job automation

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pages: 261 words: 10,785

The Lights in the Tunnel by Martin Ford

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Albert Einstein, Bill Joy: nanobots, Black-Scholes formula, call centre, cloud computing, collateralized debt obligation, commoditize, creative destruction, credit crunch, double helix, en.wikipedia.org, factory automation, full employment, income inequality, index card, industrial robot, inventory management, invisible hand, Isaac Newton, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, knowledge worker, low skilled workers, mass immigration, moral hazard, pattern recognition, prediction markets, Productivity paradox, Ray Kurzweil, Search for Extraterrestrial Intelligence, Silicon Valley, Stephen Hawking, strong AI, superintelligent machines, technological singularity, Thomas L Friedman, Turing test, Vernor Vinge, War on Poverty

Machines used on assembly lines, farm equipment, and heavy earth moving equipment are all technologies that have displaced millions of workers in the past. As history has shown, repetitive motion manufacturing jobs are among the easiest to automate. In fact, as I mentioned, this is how the Luddite movement got started back in 1811. However, the merger of mechanics and computer technology into the field of robotics will almost certainly impact an unprecedented number and types of jobs. Whether a specific hardware job is difficult or easy to automate really depends on the combination of skills and manual dexterity required. For an example of a job that is very difficult to automate, let’s consider an auto mechanic. A mechanic obviously requires a great deal of hand-eye coordination. He or she has to work on thousands of different parts in a variety of different engines, often in highly varied states of repair.

Copyrighted Material – Paperback/Kindle available @ Amazon The Tunnel / 21 A Reality Check Clearly, our simulation did not turn out well. Perhaps our initial assumption about jobs being automated was wrong. But, again, let’s leave that for the next chapter. In the meantime, we might wonder if we have made a mistake somewhere in the simulation. Let’s see if we can perform some type of “reality check” on our result. Perhaps we can look to history to see if there is anything in the past that might support what we sawhappen in our simulation. Let’s leave our tunnel and travel back in time to the year 1860. In the southern part of the United States, we knowwill find the greatest injustice ever perpetrated in the history of our nation. Here, long before the new light of advanced technology first began to shine, men had discovered a far more primitive and perverse form of job automation. The injustice and moral outrage associated with slavery rightly attracts nearly all of our attention.

As we saw with the radiologist and the lawyer, once significant portions of jobs can be automated, the number of workers employed will immediately begin to fall. The U.S. Small Business Administration estimates that businesses with fewer than 500 employees have generated from 60-80 percent of all job Copyrighted Material – Paperback/Kindle available @ Amazon Acceleration / 75 growth over the past decade.25 As it becomes easier and cheaper for business owners to employ automation and offshoring, we may well find that these practices will become a significant drag on America’s primary job creation engine. “Hardware” Jobs and Robotics A “hardware” job is a job that requires some investment in mechanical or robotic technologies in order for the job to be automated. The automation of hardware jobs started long before the computer revolution.


pages: 484 words: 104,873

Rise of the Robots: Technology and the Threat of a Jobless Future by Martin Ford

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3D printing, additive manufacturing, Affordable Care Act / Obamacare, AI winter, algorithmic trading, Amazon Mechanical Turk, artificial general intelligence, assortative mating, autonomous vehicles, banking crisis, basic income, Baxter: Rethink Robotics, Bernie Madoff, Bill Joy: nanobots, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chris Urmson, Clayton Christensen, clean water, cloud computing, collateralized debt obligation, commoditize, computer age, creative destruction, debt deflation, deskilling, diversified portfolio, Erik Brynjolfsson, factory automation, financial innovation, Flash crash, Fractional reserve banking, Freestyle chess, full employment, Goldman Sachs: Vampire Squid, Gunnar Myrdal, High speed trading, income inequality, indoor plumbing, industrial robot, informal economy, iterative process, Jaron Lanier, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Kenneth Arrow, Khan Academy, knowledge worker, labor-force participation, labour mobility, liquidity trap, low skilled workers, low-wage service sector, Lyft, manufacturing employment, Marc Andreessen, McJob, moral hazard, Narrative Science, Network effects, new economy, Nicholas Carr, Norbert Wiener, obamacare, optical character recognition, passive income, Paul Samuelson, performance metric, Peter Thiel, Plutocrats, plutocrats, post scarcity, precision agriculture, price mechanism, Ray Kurzweil, rent control, rent-seeking, reshoring, RFID, Richard Feynman, Richard Feynman, Rodney Brooks, secular stagnation, self-driving car, Silicon Valley, Silicon Valley startup, single-payer health, software is eating the world, sovereign wealth fund, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, Steven Pinker, strong AI, Stuxnet, technological singularity, telepresence, telepresence robot, The Bell Curve by Richard Herrnstein and Charles Murray, The Coming Technological Singularity, The Future of Employment, Thomas L Friedman, too big to fail, Tyler Cowen: Great Stagnation, union organizing, Vernor Vinge, very high income, Watson beat the top human players on Jeopardy!, women in the workforce

Barra also noted that Google already has “near perfect” real-time voice translation between English and Portuguese.53 As more and more routine white-collar jobs fall to automation in countries throughout the world, it seems inevitable that competition will intensify to land one of the dwindling number of positions that remain beyond the reach of the machines. The very smartest people will have a significant advantage, and they won’t hesitate to look beyond national borders. In the absence of barriers to virtual immigration, the employment prospects for nonelite college-educated workers in developed economies could turn out to be pretty grim. Education and Collaboration with the Machines As technology advances and more jobs become susceptible to automation, the conventional solution has always been to offer workers more education and training so that they can step into to new, higher-skill roles.

That’s made especially likely as the “big data” phenomenon continues to unfold: organizations are collecting incomprehensible amounts of information about nearly every aspect of their operations, and a great many jobs and tasks are likely to be encapsulated in that data—waiting for the day when a smart machine learning algorithm comes along and begins schooling itself by delving into the record left by its human predecessors. The upshot of all this is that acquiring more education and skills will not necessarily offer effective protection against job automation in the future. As an example, consider radiologists, medical doctors who specialize in the interpretation of medical images. Radiologists require a tremendous amount of training, typically a minimum of thirteen years beyond high school. Yet, computers are rapidly getting better at analyzing images. It’s quite easy to imagine that someday, in the not too distant future, radiology will be a job performed almost exclusively by machines.

Fruits and vegetables are easily damaged and often need to be selected based on color or softness. For a machine, visual recognition is a significant challenge: lighting conditions can be highly variable, and individual fruits can be in a variety of orientations and may be partly or even completely obscured by leaves. The same innovations that are advancing the robotics frontier in factory and warehouse settings are finally making many of these remaining agricultural jobs susceptible to automation. Vision Robotics, a company based in San Diego, California, is developing an octopus-like orange harvesting machine. The robot will use three-dimensional machine vision to make a computer model of an entire orange tree and then store the location of each fruit. That information will then be passed on to the machine’s eight robotic arms, which will rapidly harvest the oranges.33 Boston-area start-up Harvest Automation is initially focused on building robots to automate operations in nurseries and greenhouses; the company estimates that manual labor accounts for over 30 percent of the cost of growing ornamental plants.

The Economic Singularity: Artificial intelligence and the death of capitalism by Calum Chace

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3D printing, additive manufacturing, agricultural Revolution, AI winter, Airbnb, artificial general intelligence, augmented reality, autonomous vehicles, banking crisis, basic income, Baxter: Rethink Robotics, Berlin Wall, Bernie Sanders, bitcoin, blockchain, call centre, Chris Urmson, congestion charging, credit crunch, David Ricardo: comparative advantage, Douglas Engelbart, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Flynn Effect, full employment, future of work, gender pay gap, gig economy, Google Glasses, Google X / Alphabet X, ImageNet competition, income inequality, industrial robot, Internet of things, invention of the telephone, invisible hand, James Watt: steam engine, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, knowledge worker, lifelogging, lump of labour, Lyft, Marc Andreessen, Mark Zuckerberg, Martin Wolf, McJob, means of production, Milgram experiment, Narrative Science, natural language processing, new economy, Occupy movement, Oculus Rift, PageRank, pattern recognition, post scarcity, post-industrial society, precariat, prediction markets, QWERTY keyboard, railway mania, RAND corporation, Ray Kurzweil, RFID, Rodney Brooks, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, software is eating the world, speech recognition, Stephen Hawking, Steve Jobs, TaskRabbit, technological singularity, The Future of Employment, Thomas Malthus, transaction costs, Tyler Cowen: Great Stagnation, Uber for X, universal basic income, Vernor Vinge, working-age population, Y Combinator, young professional

Yampolskiy, Professor of Computer Engineering and Computer Science, Director of Cybersecurity lab, Author of Artificial Superintelligence: a Futuristic Approach Unprecedented productivity gains and unlimited leisure—what could possibly go wrong? Everything, says Calum Chace, if we don’t evolve a social system suited to the inevitable world of connected intelligent systems. It’s a failure of imagination to debate whether there will be jobs for humans in the automated world, Chace argues - we must look farther and ask how we will organize society when labor is not necessary to provide for the necessities of life. Find an answer, and life improves for all; without one, society collapses. Read this book to understand how social and technological forces will conspire to change the world—and the problems we need to solve to achieve the promise of the Economic Singularity.

Automated controllers which were able to modify the operation more flexibly became increasingly common in the early 20th century, but the start-stop decisions were still normally made by humans. In 1968 the first programmable logic controllers (PLCs) were introduced[xv]. These are rudimentary digital computers which allow far more flexibility in the way an electrochemical process operates, and eventually general-purpose computers were applied to the job. The advantages of process automation are clear: it can make an operation faster, cheaper, and more consistent, and it can raise quality. The disadvantages are the initial investment, which can be substantial, and the fact that close supervision is often necessary. Paradoxically, the more efficient an automated system becomes, the more crucial the contribution of the human operators. If an automated system falls into error it can waste an enormous amount of resources and perhaps cause significant damage before it is shut down.

They don't hold out much more hope for their other principal suggested remedy: “education alone is unlikely to solve the problem of surging inequality, [but] it remains the most important factor.” Gartner Gartner is the world’s leading technology market research and advisory consultancy. At its annual conference in October 2014, its research director Peter Sondergaard declared that one in three human jobs would be automated by 2025.[l] "New digital businesses require less labor; machines will make sense of data faster than humans can." He described smart machines as an example of a “super class” of technologies which carry out a wide variety of tasks, both physical and intellectual. He illustrated the case by pointing out that machines have been grading multiple choice examinations for years, but they are now moving on to essays and unstructured text.


pages: 347 words: 97,721

Only Humans Need Apply: Winners and Losers in the Age of Smart Machines by Thomas H. Davenport, Julia Kirby

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AI winter, Andy Kessler, artificial general intelligence, asset allocation, Automated Insights, autonomous vehicles, basic income, Baxter: Rethink Robotics, business intelligence, business process, call centre, carbon-based life, Clayton Christensen, clockwork universe, commoditize, conceptual framework, dark matter, David Brooks, deliberate practice, deskilling, digital map, Douglas Engelbart, Edward Lloyd's coffeehouse, Elon Musk, Erik Brynjolfsson, estate planning, fixed income, follow your passion, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, game design, general-purpose programming language, Google Glasses, Hans Lippershey, haute cuisine, income inequality, index fund, industrial robot, information retrieval, intermodal, Internet of things, inventory management, Isaac Newton, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Khan Academy, knowledge worker, labor-force participation, lifelogging, loss aversion, Mark Zuckerberg, Narrative Science, natural language processing, Norbert Wiener, nuclear winter, pattern recognition, performance metric, Peter Thiel, precariat, quantitative trading / quantitative finance, Ray Kurzweil, Richard Feynman, Richard Feynman, risk tolerance, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, six sigma, Skype, speech recognition, spinning jenny, statistical model, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, superintelligent machines, supply-chain management, transaction costs, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, Works Progress Administration, Zipcar

As intelligent technologies take over more and more of the decision-making territory once occupied by humans, are you taking any action? Are you sufficiently aware of the signs that you should? To help you get the head start you may need, here are the signs that it’s time to fly the nest. All of them are evidence that a knowledge worker’s job is on the path to automation. 1. There are automated systems available today to do some of its core tasks. The strongest evidence that automation will increasingly threaten a job is the existence of an automated system today that performs all or part of its core function. If we were radiologists or pathologists, for example, we’d be worried about the computer-aided detection systems that read images and detect signs of problems in mammography images or Pap smears. If we were IT operations engineers, we’d be worried about the systems at Facebook that let one engineer run 25,000 servers.

., 61–63, 128–29, 204–8, 223–24 business process management, 40 codified tasks and, 12–13, 14, 27–28, 30 content transmission and, 19–20 eras of, 2–5 government policies and, 229–43 income inequality and, 228–29 “isolation syndrome,” 24 job losses and, 1–6, 8, 30, 78, 150–51, 167, 223–24, 226, 227, 238 jobs resistant to, 153–75 process automation, 48–49 “race against the machine,” 8, 29 reductions in cost and time, 48, 49 regulated sectors and legal constraints on, 213–15 repetitive task, 42, 47–48, 49, 50 robotic process, 48–49, 187, 221, 222–23 “rule engines,” 47 sectors using, 1, 11–12, 13, 18, 74, 201–3 (see also specific industries) signs of coming automation, 19–22 Stepping Forward with, 176–200 Stepping In with, 134–52 Stepping Up and, 91–95 strategy of, as self-defeating, 204–8 strongest evidence of job threat, 19 Automation Anywhere, 48, 216 automotive sector, 1 Autor, David, 70–71 Balaporia, Zahir, 189–91 Bankrate.com, 96 Bathgate, Alastair, 156, 157 Baylor College of Medicine, 212 Beaudry, Paul, 6, 24 Belmont, Chris, 209 Berg company, 60–61 Berlin, Isaiah, 171 Bernanke, Ben, 28, 42, 73 Bernaski, Michael, 79, 80, 81, 82, 187 Bessen, James, 133, 233 Betterment, 86–87, 198 big-picture perspective, 71, 75, 76–77, 84, 91, 92, 99, 100, 155 Stepping Up and, 98–100 Binsted, Kim, 125 “black box,” 95, 134, 139, 148, 192, 198 Blanke, Jennifer, 7 Blue Prism, 49, 156, 216, 221 Bohrer, Abram, 159 Bostrom, Nick, 226, 227 Brackett, Glenn, 128 Braverman, Harry, 15–16 Breaking Bad (TV show), 172 Brem, Rachel, 181–82 Bridgewater Associates, 92–93 Brooks, David, 241 Brooks, Rodney, 170, 182 Brown, John Seely, 237 Brynjolfsson, Erik, 6, 8, 27, 74 Bryson, Joanna J., 226 Buehner, Carl, 120 Buffett, Warren, 244 Bush, Vannevar, 64, 248 Bustarret, Claire, 154 BYOD (Bring Your Own Device), 13 Cameron, James, 165–66 Carey, Greg, 154, 156, 172–73 Carr, Nick, 162 CastingWords, 168 Catanzaro, Sandro, 179–80, 193 Cathcart, Ron, 89–91, 95 Cerf, Vint, 248 Chambers, Joshua, 250 Charles Schwab, 88 chess, 74–76 Chi, Michelene, 163 Chicago Mercantile Exchange, 11–12 Chilean miners, 201–2 China, 239 Chiriac, Marcel, 217 Circle (Internet start-up), 146 Cisco, 43 Civilian Conservation Corps (CCC), 238 “Claiming our Humanity in the Digital Age,” 248 Class Dojo, 141 Cleveland Clinic, 54 Clifton, Jim, 8 Clinton, Bill, 108 Clockwork Universe, The (Dolnick), 169–70 Codelco/Codelco Digital, 40, 201–3 Cognex, 47 CognitiveScale, 45, 194, 209 cognitive technologies, 4–5, 32, 33–58.

Thanks, Judah Curiosity getting the best of him, Tom looked up the company in Amy’s email extension, @x.ai. It turns out X.ai is a company that uses “natural language processing” software to interpret text and schedule meetings via email. “Amy,” in other words, is automated. Meanwhile, other tools such as email and voice mail, word processing, online travel sites, and Internet search applications have been chipping away the rest of what used to be a secretarial job. Era Two automation doesn’t only affect office workers. It washes across the entire services-based economy that arose after massive productivity gains wiped out jobs in agriculture, then manufacturing. Many modern jobs are transactional service jobs—that is, they feature people helping customers access what they need from complex business systems. But whether the customer is buying an airline ticket, ordering a meal, or making an appointment, these transactions are so routinized that they are simple to translate into code.


pages: 719 words: 181,090

Site Reliability Engineering by Betsy Beyer, Chris Jones, Jennifer Petoff, Niall Richard Murphy

Air France Flight 447, anti-pattern, barriers to entry, business intelligence, business process, Checklist Manifesto, cloud computing, combinatorial explosion, continuous integration, correlation does not imply causation, crowdsourcing, database schema, defense in depth, DevOps, en.wikipedia.org, fault tolerance, Flash crash, George Santayana, Google Chrome, Google Earth, job automation, job satisfaction, linear programming, load shedding, loose coupling, meta analysis, meta-analysis, minimum viable product, MVC pattern, performance metric, platform as a service, revision control, risk tolerance, side project, six sigma, the scientific method, Toyota Production System, trickle-down economics, web application, zero day

Beyond a certain volume of changes, it is infeasible for production-wide changes to be accomplished manually, and at some time before that point, it’s a waste to have manual oversight for a process where a large proportion of the changes are either trivial or accomplished successfully by basic relaunch-and-check strategies. Let’s use internal case studies to illustrate some of the preceding points in detail. The first case study is about how, due to some diligent, far-sighted work, we managed to achieve the self-professed nirvana of SRE: to automate ourselves out of a job. Automate Yourself Out of a Job: Automate ALL the Things! For a long while, the Ads products at Google stored their data in a MySQL database. Because Ads data obviously has high reliability requirements, an SRE team was charged with looking after that infrastructure. From 2005 to 2008, the Ads Database mostly ran in what we considered to be a mature and managed state. For example, we had automated away the worst, but not all, of the routine work for standard replica replacements.

Index Symbols /varz HTTP handler, Instrumentation of Applications A abusive client behavior, Dealing with Abusive Client Behavior access control, Enforcement of Policies and Procedures ACID datastore semantics, Managing Critical State: Distributed Consensus for Reliability, Choosing a Strategy for Superior Data Integrity acknowledgments, Acknowledgments-Acknowledgments adaptive throttling, Client-Side Throttling Ads Database, Automate Yourself Out of a Job: Automate ALL the Things!-Automate Yourself Out of a Job: Automate ALL the Things! AdSense, Other service metrics aggregate availability equation, Measuring Service Risk, Availability Table aggregation, Rule Evaluation, Aggregation agility vs. stability, System Stability Versus Agility(see also software simplicity) Alertmanager service, Alerting alertsdefined, Definitions false-positive, Tagging software for, Monitoring and Alerting(see also Borgmon; time-series monitoring) anacron, Reliability Perspective Apache Mesos, Managing Machines App Engine, Case Study archives vs. backups, Backups Versus Archives asynchronous distributed consensus, How Distributed Consensus Works atomic broadcast systems, Reliable Distributed Queuing and Messaging attribution policy, Using Code Examples automationapplying to cluster turnups, Soothing the Pain: Applying Automation to Cluster Turnups-Service-Oriented Cluster-Turnup vs. autonomous systems, The Evolution of Automation at Google benefits of, The Value of Automation-The Value for Google SRE best practices for change management, Change Management Borg example, Borg: Birth of the Warehouse-Scale Computer cross-industry lessons, Automating Away Repetitive Work and Operational Overhead database example, Automate Yourself Out of a Job: Automate ALL the Things!

AdSense, Other service metrics aggregate availability equation, Measuring Service Risk, Availability Table aggregation, Rule Evaluation, Aggregation agility vs. stability, System Stability Versus Agility(see also software simplicity) Alertmanager service, Alerting alertsdefined, Definitions false-positive, Tagging software for, Monitoring and Alerting(see also Borgmon; time-series monitoring) anacron, Reliability Perspective Apache Mesos, Managing Machines App Engine, Case Study archives vs. backups, Backups Versus Archives asynchronous distributed consensus, How Distributed Consensus Works atomic broadcast systems, Reliable Distributed Queuing and Messaging attribution policy, Using Code Examples automationapplying to cluster turnups, Soothing the Pain: Applying Automation to Cluster Turnups-Service-Oriented Cluster-Turnup vs. autonomous systems, The Evolution of Automation at Google benefits of, The Value of Automation-The Value for Google SRE best practices for change management, Change Management Borg example, Borg: Birth of the Warehouse-Scale Computer cross-industry lessons, Automating Away Repetitive Work and Operational Overhead database example, Automate Yourself Out of a Job: Automate ALL the Things!-Automate Yourself Out of a Job: Automate ALL the Things! Diskerase example, Recommendations focus on reliability, Reliability Is the Fundamental Feature Google's approach to, The Value for Google SRE hierarchy of automation classes, A Hierarchy of Automation Classes recommendations for enacting, Recommendations specialized application of, The Inclination to Specialize use cases for, The Use Cases for Automation-A Hierarchy of Automation Classes automation tools, Testing Scalable Tools autonomous systems, The Evolution of Automation at Google Auxon case study, Auxon Case Study: Project Background and Problem Space-Our Solution: Intent-Based Capacity Planning, Introduction to Auxon-Introduction to Auxon availability, Indicators, Choosing a Strategy for Superior Data Integrity(see also service availability) availability table, Availability Table B B4 network, Hardware backend servers, Our Software Infrastructure, Load Balancing in the Datacenter backends, fake, Production Probes backups (see data integrity) Bandwidth Enforcer (BwE), Networking barrier tools, Testing Scalable Tools, Testing Disaster, Distributed Coordination and Locking Services batch processing pipelines, First Layer: Soft Deletion batching, Eliminate Batch Load, Batching, Drawbacks of Periodic Pipelines in Distributed Environments Bazel, Building best practicescapacity planning, Capacity Planning for change management, Change Management error budgets, Error Budgets failures, Fail Sanely feedback, Introducing a Postmortem Culture for incident management, In Summary monitoring, Monitoring overloads and failure, Overloads and Failure postmortems, Google’s Postmortem Philosophy-Collaborate and Share Knowledge, Postmortems reward systems, Introducing a Postmortem Culture role of release engineers in, The Role of a Release Engineer rollouts, Progressive Rollouts service level objectives, Define SLOs Like a User team building, SRE Teams bibliography, Bibliography Big Data, Origin of the Pipeline Design Pattern Bigtable, Storage, Target level of availability, Bigtable SRE: A Tale of Over-Alerting bimodal latency, Bimodal latency black-box monitoring, Definitions, Black-Box Versus White-Box, Black-Box Monitoring blameless cultures, Google’s Postmortem Philosophy Blaze build tool, Building Blobstore, Storage, Choosing a Strategy for Superior Data Integrity Borg, Hardware-Managing Machines, Borg: Birth of the Warehouse-Scale Computer-Borg: Birth of the Warehouse-Scale Computer, Drawbacks of Periodic Pipelines in Distributed Environments Borg Naming Service (BNS), Managing Machines Borgmon, The Rise of Borgmon-Ten Years On…(see also time-series monitoring) alerting, Monitoring and Alerting, Alerting configuration, Maintaining the Configuration rate() function, Rule Evaluation rules, Rule Evaluation-Rule Evaluation sharding, Sharding the Monitoring Topology timeseries arena, Storage in the Time-Series Arena vectors, Labels and Vectors-Labels and Vectors break-glass mechanisms, Expect Testing Fail build environments, Creating a Test and Build Environment business continuity, Ensuring Business Continuity Byzantine failures, How Distributed Consensus Works, Number of Replicas C campuses, Hardware canarying, Motivation for Error Budgets, What we learned, Canary test, Gradual and Staged Rollouts CAP theorem, Managing Critical State: Distributed Consensus for Reliability CAPA (corrective and preventative action), Postmortem Culture capacity planningapproaches to, Practices best practices for, Capacity Planning Diskerase example, Recommendations distributed consensus systems and, Capacity and Load Balancing drawbacks of "queries per second", The Pitfalls of “Queries per Second” drawbacks of traditional plans, Brittle by nature further reading on, Practices intent-based (see intent-based capacity planning) mandatory steps for, Demand Forecasting and Capacity Planning preventing server overload with, Preventing Server Overload product launches and, Capacity Planning traditional approach to, Traditional Capacity Planning cascading failuresaddressing, Immediate Steps to Address Cascading Failures-Eliminate Bad Traffic causes of, Causes of Cascading Failures and Designing to Avoid Them-Service Unavailability defined, Addressing Cascading Failures, Capacity and Load Balancing factors triggering, Triggering Conditions for Cascading Failures overview of, Closing Remarks preventing server overload, Preventing Server Overload-Always Go Downward in the Stack testing for, Testing for Cascading Failures-Test Noncritical Backends(see also overload handling) change management, Change Management(see also automation) change-induced emergencies, Change-Induced Emergency-What we learned changelists (CLs), Our Development Environment Chaos Monkey, Testing Disaster checkpoint state, Testing Disaster cherry picking tactic, Hermetic Builds Chubby lock service, Lock Service, System Architecture Patterns for Distributed Consensusplanned outage, Objectives, SLOs Set Expectations client tasks, Load Balancing in the Datacenter client-side throttling, Client-Side Throttling clients, Our Software Infrastructure clock drift, Managing Critical State: Distributed Consensus for Reliability Clos network fabric, Hardware cloud environmentdata integrity strategies, Choosing a Strategy for Superior Data Integrity, Challenges faced by cloud developers definition of data integrity in, Data Integrity’s Strict Requirements evolution of applications in, Choosing a Strategy for Superior Data Integrity technical challenges of, Requirements of the Cloud Environment in Perspective clustersapplying automation to turnups, Soothing the Pain: Applying Automation to Cluster Turnups-Service-Oriented Cluster-Turnup cluster management solution, Drawbacks of Periodic Pipelines in Distributed Environments defined, Hardware code samples, Using Code Examples cognitive flow state, Cognitive Flow State cold caching, Slow Startup and Cold Caching colocation facilities (colos), Recommendations Colossus, Storage command posts, A Recognized Command Post communication and collaborationblameless postmortems, Collaborate and Share Knowledge case studies, Case Study of Collaboration in SRE: Viceroy-Case Study: Migrating DFP to F1 importance of, Conclusion with Outalator, Reporting and communication outside SRE team, Collaboration Outside SRE position of SRE in Google, Communication and Collaboration in SRE production meetings (see production meetings) within SRE team, Collaboration within SRE company-wide resilience testing, Practices compensation structure, Compensation computational optimization, Our Solution: Intent-Based Capacity Planning configuration management, Configuration Management, Change-Induced Emergency, Integration, Process Updates configuration tests, Configuration test consensus algorithmsEgalitarian Paxos, Stable Leaders Fast Paxos, Reasoning About Performance: Fast Paxos, The Use of Paxos improving performance of, Distributed Consensus Performance Multi-Paxos, Disk Access Paxos, How Distributed Consensus Works, Disk Access Raft, Multi-Paxos: Detailed Message Flow, Stable Leaders Zab, Stable Leaders(see also distributed consensus systems) consistencyeventual, Managing Critical State: Distributed Consensus for Reliability through automation, Consistency consistent hashing, Load Balancing at the Virtual IP Address constraints, Laborious and imprecise Consul, System Architecture Patterns for Distributed Consensus consumer services, identifying risk tolerance of, Identifying the Risk Tolerance of Consumer Services-Other service metrics continuous build and deploymentBlaze build tool, Building branching, Branching build targets, Building configuration management, Configuration Management deployment, Deployment packaging, Packaging Rapid release system, Continuous Build and Deployment, Rapid testing, Testing typical release process, Rapid contributors, Acknowledgments-Acknowledgments coroutines, Origin of the Pipeline Design Pattern corporate network security, Practices correctness guarantees, Workflow Correctness Guarantees correlation vs. causation, Theory costsavailability targets and, Cost, Cost direct, The Sysadmin Approach to Service Management of failing to embrace risk, Managing Risk indirect, The Sysadmin Approach to Service Management of sysadmin management approach, The Sysadmin Approach to Service Management CPU consumption, The Pitfalls of “Queries per Second”, CPU, Overload Behavior and Load Tests crash-fail vs. crash-recover algorithms, How Distributed Consensus Works cronat large scale, Running Large Cron building at Google, Building Cron at Google-Running Large Cron idempotency, Cron Jobs and Idempotency large-scale deployment of, Cron at Large Scale leader and followers, The leader overview of, Summary Paxos algorithm and, The Use of Paxos-Storing the State purpose of, Distributed Periodic Scheduling with Cron reliability applications of, Reliability Perspective resolving partial failures, Resolving partial failures storing state, Storing the State tracking cron job state, Tracking the State of Cron Jobs uses for, Cron cross-industry lessonsApollo 8, Preface comparative questions presented, Lessons Learned from Other Industries decision-making skills, Structured and Rational Decision Making-Structured and Rational Decision Making Google's application of, Conclusions industry leaders contributing, Meet Our Industry Veterans key themes addressed, Lessons Learned from Other Industries postmortem culture, Postmortem Culture-Postmortem Culture preparedness and disaster testing, Preparedness and Disaster Testing-Defense in Depth and Breadth repetitive work/operational overhead, Automating Away Repetitive Work and Operational Overhead current state, exposing, Examine D D storage layer, Storage dashboardsbenefits of, Why Monitor?


pages: 215 words: 56,215

The Second Intelligent Species: How Humans Will Become as Irrelevant as Cockroaches by Marshall Brain

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Amazon Web Services, basic income, clean water, cloud computing, computer vision, digital map, en.wikipedia.org, full employment, income inequality, job automation, knowledge worker, mutually assured destruction, Occupy movement, Search for Extraterrestrial Intelligence, self-driving car, Stephen Hawking, working poor

Millions of construction workers will be replaced. Factories are already highly automated. For example, in a car factory, robots do all the welding and painting. Many of the factory jobs that remain have not been automated because they require vision. Putting a wiring harness into an automobile on an assembly line is done by humans today because humans can see and easily handle flexible materials. Most other human jobs that remain in an auto assembly factory require vision in the same way. Once robots can see, all of those factory jobs will start going to robots just like all of the welding, painting and machining jobs that are already automated. Think about all of the custodial jobs in hotels, arenas, college campuses, office parks and homes. With robots that can see, it is possible to clean things, and all of the custodians, janitors and maids start getting replaced.

What if there is no economic downturn, but instead new technology comes along that eliminates 200,000 jobs? For example, imagine that one company develops self-driving trucks and that they eliminate all of the truck driver jobs, while another company develops automated tools that eliminate many of the remaining factory jobs, and another company develops brick-laying, painting and roofing robots that eliminate quite a few construction jobs, plus another company develops a kiosk system that eliminates the jobs of many waiters and waitresses in restaurants, and so on. Now the society has a permanent loss of 200,000 jobs, with 200,000 homeless people and with more pressure on jobs from other forms of automation that are rapidly advancing. How does the society deal with this situation? What if many of the people in the society stop worrying and caring about the design of the society?

Eventually, the only people who will still have jobs in the fast food industry will be the senior management team at corporate headquarters, and they will be making staggering amounts of money. The same sort of thing will happen in many other industries: retail stores, hotels, airports, factories, construction sites, delivery companies, education and so on. All of these jobs will evaporate at approximately the same time, leaving all of those workers unemployed. But who will be first? Which large group of employees will lose their jobs first as robots and automation start taking jobs away from human beings? It is likely to be a million or more truck drivers.... Chapter 4 - The Aborted Trucker Riots How long will it take before computer consciousness arises and begins the process of making human beings completely irrelevant? We don't know. It will likely take a couple of decades, for example a 2040 timeframe. But 30 to 40 years is likely the maximum length of time, for reasons we explored in the Chapters 2 and 3.


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Four Futures: Life After Capitalism by Peter Frase

3D printing, Airbnb, basic income, bitcoin, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, cryptocurrency, deindustrialization, Edward Snowden, Erik Brynjolfsson, Ferguson, Missouri, fixed income, full employment, future of work, high net worth, income inequality, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), iterative process, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, litecoin, mass incarceration, means of production, Norbert Wiener, Occupy movement, pattern recognition, peak oil, Plutocrats, plutocrats, postindustrial economy, price mechanism, private military company, Ray Kurzweil, Robert Gordon, Second Machine Age, self-driving car, sharing economy, Silicon Valley, smart meter, TaskRabbit, technoutopianism, The Future of Employment, Thomas Malthus, Tyler Cowen: Great Stagnation, universal basic income, Wall-E, Watson beat the top human players on Jeopardy!, We are the 99%, Wolfgang Streeck

The folk tale of John Henry and the steam hammer, which originated in the nineteenth century, describes a railroad worker who tries to race against a steel powered drill and wins—only to drop dead from the effort. But several factors have come together to accentuate worries about technology and its effect on labor. The persistently weak post-recession labor market has produced a generalized background anxiety about job loss. Automation and computerization are beginning to reach into professional and creative industries that long seemed immune, threatening the jobs of the very journalists who cover these issues. And the pace of change at least seems, to many, to be faster than ever. The “second machine age” is a concept promoted by Brynjolfsson and McAfee. In their book of the same name, they argue that just as the first machine age—the Industrial Revolution—replaced human muscle with machine power, computerization is allowing us to greatly magnify, or even replace, “the ability to use our brains to understand and shape our environments.”6 In that book and its predecessor, Race Against the Machine, Brynjolfsson and McAfee argue that computers and robots are rapidly permeating every part of the economy, displacing labor from high- and low-skill functions alike.

But a corollary to this principle is that, if wages begin to rise and labor markets tighten, employers will start to turn to the new technologies that are currently being developed, rather than pay the cost of additional labor. As I argue in the following sections, the real impediments to tight labor markets are currently political, not technological. AUTOMATION’S ETERNAL RETURN Mainstream economists have for generations made the same argument about the supposed danger that automation poses to labor. If some jobs are automated, they argue, labor is freed up for other, new, and perhaps better kinds of work. They point to agriculture, which once occupied most of the workforce but now occupies only about 2 percent of it in a country like the United States. The decline of agricultural employment freed up workers who would go into the factories and make up the great industrial manufacturing economy of the mid-twentieth century.

Supporters of this position can point to previous waves of anxiety about automation, such as the one in the 1990s that produced works like Jeremy Rifkin’s The End of Work and Stanley Aronowitz and Bill DeFazio’s The Jobless Future.17 As early as 1948, the mathematician and cyberneticist Norbert Weiner warned in his book Cybernetics that in the “second, cybernetic industrial revolution,” we were approaching a society in which “the average human being of mediocre attainments or less has nothing to sell that it is worth anyone’s money to buy.”18 While many jobs have indeed been lost to automation, and jobless rates have risen and fallen with the business cycle, the social crisis of extreme mass unemployment, which many of these authors anticipated, has failed to arrive. Of course, this is the kind of argument that can only be made from a great academic height, while ignoring the pain and disruption caused to actual workers who are displaced, whether or not they can eventually find new work.


pages: 144 words: 43,356

Surviving AI: The Promise and Peril of Artificial Intelligence by Calum Chace

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3D printing, Ada Lovelace, AI winter, Airbnb, artificial general intelligence, augmented reality, barriers to entry, basic income, bitcoin, blockchain, brain emulation, Buckminster Fuller, cloud computing, computer age, computer vision, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, dematerialisation, discovery of the americas, disintermediation, don't be evil, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, everywhere but in the productivity statistics, Flash crash, friendly AI, Google Glasses, industrial robot, Internet of things, invention of agriculture, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, life extension, low skilled workers, Mahatma Gandhi, means of production, mutually assured destruction, Nicholas Carr, pattern recognition, peer-to-peer, peer-to-peer model, Peter Thiel, Ray Kurzweil, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley ideology, Skype, South Sea Bubble, speech recognition, Stanislav Petrov, Stephen Hawking, Steve Jobs, strong AI, technological singularity, The Future of Employment, theory of mind, Turing machine, Turing test, universal basic income, Vernor Vinge, wage slave, Wall-E, zero-sum game

Military leaders in an age where most combatants are robots will have a clearer idea of whether their forces are a match for those of the opposition. The leaders with the weaker forces may feel less inclined to start a war they can be fairly confident they will lose. 3.3 – Economic singularity In the medium term, AI presents economists, business people and policy makers with an even bigger concern than digital disruption. It may render most of us unemployed, and indeed unemployable, because our jobs have been automated. Automation Automation has been a feature of human civilisation since at least the early industrial revolution. In the 15th century, Dutch workers threw their shoes into textile looms to break them. (Their shoes were called sabots, which is a possible etymology for the word “saboteur”.) The development of engines powered by steam and then coal raised automation to a new level. The classic example is the mechanisation of agriculture, which accounted for 41% of US employment in 1900, and only 2% in 2000.

This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.” (19) Decades later, in the late 1970s, a powerful BBC Horizon documentary called Now the Chips are Down alerted a new generation to the idea (and showcased some truly appalling ties.) (20) Up to now the replacement of humans by machines has been a gradual process. Although it has been painful for each individual who was dismissed from a particular job, there was generally the chance to retrain, or find new work elsewhere. The idea that each job lost to automation equates to a person rendered permanently unemployed is known as the Luddite Fallacy. This is unfair to the Luddites, who weren’t advancing a sociological thesis about the long-term effects of technology. They were simply protesting about the very real danger of starvation in the short term. It is also not true that Maynard Keynes argued that automation would destroy jobs any time soon.

Perhaps we can get round the problem of how professionals acquire their skills when the AI is doing all the grunt work which currently provides the training for junior doctors and lawyers. But harder to escape is the thought that the piece of analysis or decision-making that the AI can’t do today, it may well be able to do tomorrow, or the next day. Rapid job churn or economic singularity If computers steal our old jobs, perhaps we can invent lots of new ones? In the past, people whose jobs were automated turned their hands to more value-adding activity, and the net result was higher overall productivity. The children of people who did back-breaking farm work for subsistence wages moved into the cities where they earned a little more doing mundane jobs in offices and factories. Their great-grandchildren now work as social media marketers and user experience designers – jobs which their great-grandparents could not have imagined.


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Race Against the Machine: How the Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy by Erik Brynjolfsson

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Amazon Mechanical Turk, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, business process, call centre, combinatorial explosion, corporate governance, creative destruction, crowdsourcing, David Ricardo: comparative advantage, easy for humans, difficult for computers, Erik Brynjolfsson, factory automation, first square of the chessboard, first square of the chessboard / second half of the chessboard, Frank Levy and Richard Murnane: The New Division of Labor, hiring and firing, income inequality, intangible asset, job automation, John Markoff, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, Kickstarter, knowledge worker, labour mobility, Loebner Prize, low skilled workers, minimum wage unemployment, patent troll, pattern recognition, Paul Samuelson, Ray Kurzweil, rising living standards, Robert Gordon, self-driving car, shareholder value, Skype, too big to fail, Turing test, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, wealth creators, winner-take-all economy, zero-sum game

Technologies like robotics, numerically controlled machines, computerized inventory control, and automatic transcription have been substituting for routine tasks, displacing those workers. Meanwhile other technologies like data visualization, analytics, high-speed communications, and rapid prototyping have augmented the contributions of more abstract and data-driven reasoning, increasing the value of those jobs. Skill-biased technical change has also been important in the past. For most of the 19th century, about 25% of all agriculture labor threshed grain. That job was automated in the 1860s. The 20th century was marked by an accelerating mechanization not only of agriculture but also of factory work. Echoing the first Nobel Prize winner in economics, Jan Tinbergen, Harvard economists Claudia Goldin and Larry Katz described the resulting SBTC as a “race between education and technology.” Ever-greater investments in education, dramatically increasing the average educational level of the American workforce, helped prevent inequality from soaring as technology automated more and more unskilled work.


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Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence by Jerry Kaplan

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Affordable Care Act / Obamacare, Amazon Web Services, asset allocation, autonomous vehicles, bank run, bitcoin, Bob Noyce, Brian Krebs, buy low sell high, Capital in the Twenty-First Century by Thomas Piketty, combinatorial explosion, computer vision, corporate governance, crowdsourcing, en.wikipedia.org, Erik Brynjolfsson, estate planning, Flash crash, Gini coefficient, Goldman Sachs: Vampire Squid, haute couture, hiring and firing, income inequality, index card, industrial robot, information asymmetry, invention of agriculture, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, Loebner Prize, Mark Zuckerberg, mortgage debt, natural language processing, Own Your Own Home, pattern recognition, Satoshi Nakamoto, school choice, Schrödinger's Cat, Second Machine Age, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, Skype, software as a service, The Chicago School, The Future of Employment, Turing test, Watson beat the top human players on Jeopardy!, winner-take-all economy, women in the workforce, working poor, Works Progress Administration

This paper meets the requirements of ANSI/NISO Z39.48–1992 (Permanence of Paper). 10 9 8 7 6 5 4 3 2 1 For Camryn Paige Kaplan Turn your dreams into words and make them true. Contents Preface Introduction: Welcome to the Future 1. Teaching Computers to Fish 2. Teaching Robots to Heel 3. Robotic Pickpockets 4. The Gods Are Angry 5. Officer, Arrest That Robot 6. America, Land of the Free Shipping 7. America, Home of the Brave Pharaohs 8. Take This Job and Automate It 9. The Fix Is In Outroduction: Welcome to Your Children’s Future Acknowledgments Notes Index Preface I’m an optimist. Not by nature, but by U.S. government design. After Russia humiliated the United States with the 1957 launch of Sputnik, the first space satellite, the government decided that science education should be a national priority. The cold war was in full swing, and Senator John F.

These systems use enormous computing power and sophisticated adaptive AI algorithms to continuously adjust radio signals to local conditions at multiple receivers simultaneously, eliminating the need for on-premises wiring entirely.17 One such technology is DIDO (distributed input, distributed output), developed by Silicon Valley entrepreneur Steve Perlman, whose previous accomplishments include QuickTime and WebTV. If his approach wins out in the marketplace, he will add handsomely to his already vast fortune, while the 250,000 people currently employed installing and repairing wiring in the United States will be applying for entry-level jobs with Enterprise Rent-a-Car.18 8. Take This Job and Automate It Despite what you read in the press, global warming isn’t all bad, and certainly not for everyone. There will be winners and losers, depending on where you live. In my case, it’s a tad too cool around here for my taste, but luckily for me, the average temperature where I live is projected to rise several degrees over the next few decades. Sounds good; hope I live to see it. Global warming in and of itself isn’t a problem.

The Law School Admissions Council reports that applications in 2014 were down nearly 30 percent over just the previous two years, returning to levels last seen in 1977.30 New graduates can be saddled with debt of more than $150,000, while the average graduate’s starting salary in 2011 was only $60,000, down nearly 17 percent from just two years earlier.31 But they were the lucky ones. In 2009, an astounding 35 percent of newly minted law school graduates failed to find work that required them to pass the bar exam.32 There are, of course, many factors affecting job opportunities for attorneys, but automation is certainly among them. And the problems are just getting started. To date, the use of computers in the legal profession has been largely focused on the storage and management of legal documents. This reduces billable hours because you don’t have to start from scratch when drafting contracts and briefs. But a new crop of legal-tech entrepreneurs is working to greatly reduce or eliminate the need for lawyers for the most common transactions.


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The End of Nice: How to Be Human in a World Run by Robots (Kindle Single) by Richard Newton

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3D printing, Black Swan, British Empire, Buckminster Fuller, Clayton Christensen, crowdsourcing, deliberate practice, fear of failure, Filter Bubble, future of work, Google Glasses, Isaac Newton, James Dyson, Jaron Lanier, Jeff Bezos, job automation, Lean Startup, low skilled workers, Mark Zuckerberg, move fast and break things, move fast and break things, Paul Erdős, Paul Graham, recommendation engine, rising living standards, Robert Shiller, Robert Shiller, Silicon Valley, Silicon Valley startup, skunkworks, Steve Ballmer, Steve Jobs, Y Combinator

Because if these nice qualities are your strengths then, gradually and then very suddenly, they will become your weaknesses. These once-valuable qualities of rule-bound, routinised and biddable behaviour and consistent, predictable decision-making are precisely the attributes of robots and algorithms. They are not, however, the greatest strengths of humans and this is why the days of humans-as-meat-machines are drawing to a close. To save your job from automation you cannot put in more hours, run faster, make fewer mistakes, sleep any less than you do already. Steel-cased algorithms arriving at the howling speed of six-legged robot soldiers take job after job and each time they teach the lesson: the humans were mere cogs in the machine and they just got switched out. Some skills provide some protection. But for most jobs it’s temporary. Give it a year.

Sometime after that the elevator operator also bragged them too. Only to find that his new-fangled push-button lift reached the lobby and he was escorted out of the building. And the same story of woe is repeated through history by chimney sweeps, ice delivery men, punkahwallahs, bus conductors and ironmongers. Of course for you it might be true and maybe no machine can replace you. Perhaps. But if 50% of today’s jobs get automated (as an Oxford University study recently warned… and other studies predict worse outcomes) then the entire fabric of society will be utterly transformed. Those very few people whose jobs remain unchanged may discover their privileged position is as fine and grand as a proud horse harrumphing about their specialness while they stand on the hard shoulder of a motorway. Even those well-heeled fortresses of human intelligence, the blue chip management consultancy firms, are under attack.


pages: 179 words: 43,441

The Fourth Industrial Revolution by Klaus Schwab

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3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, Buckminster Fuller, call centre, clean water, collaborative consumption, commoditize, conceptual framework, continuous integration, crowdsourcing, disintermediation, distributed ledger, Edward Snowden, Elon Musk, epigenetics, Erik Brynjolfsson, future of work, global value chain, Google Glasses, income inequality, Internet Archive, Internet of things, invention of the steam engine, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, life extension, Lyft, mass immigration, megacity, meta analysis, meta-analysis, more computing power than Apollo, mutually assured destruction, Narrative Science, Network effects, Nicholas Carr, personalized medicine, precariat, precision agriculture, Productivity paradox, race to the bottom, randomized controlled trial, reshoring, RFID, rising living standards, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, smart cities, smart contracts, software as a service, Stephen Hawking, Steve Jobs, Steven Levy, Stuxnet, supercomputer in your pocket, The Future of Employment, The Spirit Level, total factor productivity, transaction costs, Uber and Lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, winner-take-all economy, women in the workforce, working-age population, Y Combinator, Zipcar

In fact, in the vast majority of cases, the fusion of digital, physical and biological technologies driving the current changes will serve to enhance human labour and cognition, meaning that leaders need to prepare workforces and develop education models to work with, and alongside, increasingly capable, connected and intelligent machines. Impact on skills In the foreseeable future, low-risk jobs in terms of automation will be those that require social and creative skills; in particular, decision-making under uncertainty and the development of novel ideas. This, however, may not last. Consider one of the most creative professions – writing – and the advent of automated narrative generation. Sophisticated algorithms can create narratives in any style appropriate to a particular audience. The content is so human-sounding that a recent quiz by The New York Times showed that when reading two similar pieces, it is impossible to tell which one has been written by a human writer and which one is the product of a robot.

Osborne, “The Future of Employment: How Susceptible Are Jobs to Computerisation?”, 17 September 2013 Positive impacts – Cost reductions – Efficiency gains – Unlocking innovation, opportunities for small business, start-ups (smaller barriers to entry, “software as a service” for everything) Negative impacts – Job losses – Accountability and liability – Change to legal, financial disclosure, risk – Job automation (refer to the Oxford Martin study) The shift in action Advances in automation were reported on by FORTUNE: “IBM’s Watson, well known for its stellar performance in the TV game show Jeopardy!, has already demonstrated a far more accurate diagnosis rate for lung cancers than humans – 90% versus 50% in some tests. The reason is data. Keeping pace with the release of medical data could take doctors 160 hours a week, so doctors cannot possibly review the amount of new insights or even bodies of clinical evidence that can give an edge in making a diagnosis.


pages: 357 words: 95,986

Inventing the Future: Postcapitalism and a World Without Work by Nick Srnicek, Alex Williams

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3D printing, additive manufacturing, air freight, algorithmic trading, anti-work, back-to-the-land, banking crisis, basic income, battle of ideas, blockchain, Bretton Woods, call centre, capital controls, carbon footprint, Cass Sunstein, centre right, collective bargaining, crowdsourcing, cryptocurrency, David Graeber, decarbonisation, deindustrialization, deskilling, Doha Development Round, Elon Musk, Erik Brynjolfsson, Ferguson, Missouri, financial independence, food miles, Francis Fukuyama: the end of history, full employment, future of work, gender pay gap, housing crisis, income inequality, industrial robot, informal economy, intermodal, Internet Archive, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, late capitalism, liberation theology, Live Aid, low skilled workers, manufacturing employment, market design, Martin Wolf, mass immigration, mass incarceration, means of production, minimum wage unemployment, Mont Pelerin Society, neoliberal agenda, New Urbanism, Occupy movement, oil shale / tar sands, oil shock, patent troll, pattern recognition, Paul Samuelson, Philip Mirowski, post scarcity, postnationalism / post nation state, precariat, price stability, profit motive, quantitative easing, reshoring, Richard Florida, rising living standards, road to serfdom, Robert Gordon, Ronald Reagan, Second Machine Age, secular stagnation, self-driving car, Slavoj Žižek, social web, stakhanovite, Steve Jobs, surplus humans, the built environment, The Chicago School, The Future of Employment, Tyler Cowen: Great Stagnation, universal basic income, wages for housework, We are the 99%, women in the workforce, working poor, working-age population

With the potential for extensive automation of work – a topic that will be discussed further in the next chapter – it is likely that we will see the following trends in the years to come: 1.The precarity of the developed economies’ working class will intensify due to the surplus global labour supply (resulting from both globalisation and automation). 2.Jobless recoveries will continue to deepen and lengthen, predominantly affecting those whose jobs can be automated at the time. 3.Slum populations will continue to grow due to the automation of low-skilled service work, and will be exacerbated by premature deindustrialisation. 4.Urban marginality in the developed economies will grow in size as low-skilled, low-wage jobs are automated. 5.The transformation of higher education into job training will be hastened in a desperate attempt to increase the supply of high-skilled workers. 6.Growth will remain slow and make the expansion of replacement jobs unlikely. 7.The changes to workfare, immigration controls and mass incarceration will deepen as those without jobs are increasingly subjected to coercive controls and survival economies.

(The racialisation of the surplus population also enabled owners to manipulate the white working class, keeping wages low and preventing unionisation.)89 As capitalism grew in the postwar era, manufacturing jobs eventually opened up to the black population, and by the mid 1950s rates of black and white youth unemployment were broadly similar.90 But then the globalisation of the labour supply wreaked havoc on low-skilled black workers. With manufacturing jobs shipped overseas or subject to automation, these workers were disproportionately affected by deindustrialisation.91 Industrial jobs left the urban centres and were replaced by service work often located in distant suburban areas.92 The urban ghettos were left to rot, becoming concentrated hubs of long-term joblessness.93 They became poverty traps, devoid of jobs, with little community support and a proliferation of underground economies.94 Entire communities were cast aside from the machinery of capitalism and left to fend for themselves with whatever means could be scraped together.

For instance, out of the US companies that could benefit from incorporating industrial robots, less than 10 per cent have done so.43 This is but one area for full automation to take hold in, and this reiterates the importance of making full automation a political demand, rather than assuming it will come about from economic necessity. A variety of policies can help in this project: more state investment, higher minimum wages and research devoted to technologies that replace rather than augment workers. In the most detailed estimates of the labour market, it is suggested that between 47 and 80 per cent of today’s jobs are capable of being automated.44 Let us take this estimate not as a deterministic prediction, but instead as the outer limit of a political project against work. We should take these numbers as a standard against which to measure our success. While full automation of the economy is presented here as an ideal and a demand, in practice it is unlikely to be fully achieved.45 In certain spheres, human labour is likely to continue for technical, economic and ethical reasons.


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The End of Work by Jeremy Rifkin

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banking crisis, Bertrand Russell: In Praise of Idleness, blue-collar work, cashless society, collective bargaining, computer age, deskilling, Dissolution of the Soviet Union, employer provided health coverage, Erik Brynjolfsson, full employment, future of work, general-purpose programming language, George Gilder, global village, hiring and firing, informal economy, interchangeable parts, invention of the telegraph, Jacques de Vaucanson, job automation, John Maynard Keynes: technological unemployment, knowledge economy, knowledge worker, land reform, low skilled workers, means of production, new economy, New Urbanism, Paul Samuelson, pink-collar, post-industrial society, Productivity paradox, Richard Florida, Ronald Reagan, Silicon Valley, speech recognition, strikebreaker, technoutopianism, Thorstein Veblen, Toyota Production System, trade route, trickle-down economics, women in the workforce, working poor, working-age population, Works Progress Administration

Management consultant Peter Drucker estimates that employment in manufacturing is going to continue dropping to less than 12 percent of the US. workforce in the next decade. 17 For most of the 1980s it was fashionable to blame the loss of manufacturing jobs in the United States on foreign competition and cheap labor markets abroad. Recently, however, economists have begun to revise their views in light of new in-depth studies of the US. manufacturing sector. Noted economists Paul R. Krugman of MIT and Robert L. Lawrence of Harvard University suggest, on the basis of extensive data, that "the concern, widely voiced during the 1950S and 1960s, that industrial workers would lose their jobs because of automation, is closer to the truth than the current preoccupation with a presumed loss of manufacturing jobs because of foreign competition."18 Although the number of blue collar workers continues to decline, manufacturing productivity is soaring. In the United States, annual productivity, which was growing at slightly over 1 percent per year in the early 1980s, has climbed to over 3 percent in the wake of the new advances in computer automation and the restructuring of the workplace.

An additional 35 million have less than a ninth-grade reading level. As educator Jonathan Kozol points out, "employment qualifications for all but a handful of domestic jobs begins at the ninth-grade level."68 For these Americans, the hope of being retrained or schooled for a new job in the elite knowledge sector is painfully out of reach. And, even if re-education and retraining on a mass scale were implemented, not enough high-tech jobs will be available in the automated economy of the twenty-first century to absorb the vast numbers of dislocated workers. THE SHRINKING PUBLIC SECTOR For the past sixty years, increased government spending has been the only viable means "to cheat the devil of ineffective demand" says economist Paul Samuelson. 69 Technological innovation, rising productivity, growing technological unemployment, and ineffective demand have characterized the American economy since the 1950S, forcing the federal government to adopt a strategy of deficit spending to create jobs, stimulate purchasing power, and boost economic growth.

During the 1980s, real hourly compensation in the High-Tech Winners and Losers 167 manufacturing sector alone decreased from $7.78 to $7.69 an hour. 5 By the end of the decade nearly 10 percent of the American workforce was unemployed, underemployed, or working part time because full-time work was unavailable, or were too discouraged to even look for ajob. 6 Between 1989 and 1993, more than 1.8 million workers lost their jobs in the manufacturing sector, many of them victims of automation, either at the hands of their American employers or by foreign companies whose more highly automated plants and cheaper operating costs forced domestic producers to downsize their operations and lay off workers. Of those who have lost their jobs to automation, only a third were able to find new jobs in the service sector, and then at a 20 percent drop in pay. 7 Government figures on employment are often misleading, masking the true dimensions of the unfolding job crisis. For example, in August 1993 the federal government announced that nearly 1,230,000 jobs had been created in the United States in the first half of 1993. What they failed to say was that 728,000 of them-nearly 60 percent-were part-time, for the most part in low-wage service industries.


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The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson, Andrew McAfee

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, access to a mobile phone, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, American Society of Civil Engineers: Report Card, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, basic income, Baxter: Rethink Robotics, British Empire, business intelligence, business process, call centre, Chuck Templeton: OpenTable, clean water, combinatorial explosion, computer age, computer vision, congestion charging, corporate governance, creative destruction, crowdsourcing, David Ricardo: comparative advantage, digital map, employer provided health coverage, en.wikipedia.org, Erik Brynjolfsson, factory automation, falling living standards, Filter Bubble, first square of the chessboard / second half of the chessboard, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, full employment, game design, global village, happiness index / gross national happiness, illegal immigration, immigration reform, income inequality, income per capita, indoor plumbing, industrial robot, informal economy, intangible asset, inventory management, James Watt: steam engine, Jeff Bezos, jimmy wales, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kevin Kelly, Khan Academy, knowledge worker, Kodak vs Instagram, law of one price, low skilled workers, Lyft, Mahatma Gandhi, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Mars Rover, mass immigration, means of production, Narrative Science, Nate Silver, natural language processing, Network effects, new economy, New Urbanism, Nicholas Carr, Occupy movement, oil shale / tar sands, oil shock, pattern recognition, Paul Samuelson, payday loans, price stability, Productivity paradox, profit maximization, Ralph Nader, Ray Kurzweil, recommendation engine, Report Card for America’s Infrastructure, Robert Gordon, Rodney Brooks, Ronald Reagan, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Simon Kuznets, six sigma, Skype, software patent, sovereign wealth fund, speech recognition, statistical model, Steve Jobs, Steven Pinker, Stuxnet, supply-chain management, TaskRabbit, technological singularity, telepresence, The Bell Curve by Richard Herrnstein and Charles Murray, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, total factor productivity, transaction costs, Tyler Cowen: Great Stagnation, Vernor Vinge, Watson beat the top human players on Jeopardy!, winner-take-all economy, Y2K

Technological Unemployment We’ve seen that the overall pie of the economy is growing, but some people, even a majority of them, can be made worse off by advances in technology. As demand falls for labor, particularly relatively unskilled labor, wages fall. But can technology actually lead to unemployment? We’re not the first people to ask these questions. In fact, they’ve been debated vigorously, even violently, for at least two hundred years. Between 1811 and 1817, a group of English textile workers whose jobs were threatened by the automated looms of the first Industrial Revolution rallied around a perhaps mythical, Robin Hood–like figure named Ned Ludd and attacked mills and machinery before being suppressed by the British government. Economists and other scholars saw in the Luddite movement an early example of a broad and important new pattern: large-scale automation entering the workplace and affecting people’s wage and employment prospects.

These new goods and services provide a path for productivity growth based on increased output rather than reduced inputs. Thus in a very real sense, as long as there are unmet needs and wants in the world, unemployment is a loud warning that we simply aren’t thinking hard enough about what needs doing. We aren’t being creative enough about solving the problems we have using the freed-up time and energy of the people whose old jobs were automated away. We can do more to invent technologies and business models that augment and amplify the unique capabilities of humans to create new sources of value, instead of automating the ones that already exist. As we will discuss further in the next chapters, this is the real challenge facing our policy makers, our entrepreneurs, and each of us individually. An Alternative Explanation: Globalization Technology isn’t the only thing transforming the economy.


pages: 370 words: 94,968

The Most Human Human: What Talking With Computers Teaches Us About What It Means to Be Alive by Brian Christian

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4chan, Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Bertrand Russell: In Praise of Idleness, carbon footprint, cellular automata, Claude Shannon: information theory, cognitive dissonance, commoditize, complexity theory, crowdsourcing, David Heinemeier Hansson, Donald Trump, Douglas Hofstadter, George Akerlof, Gödel, Escher, Bach, high net worth, Isaac Newton, Jacques de Vaucanson, Jaron Lanier, job automation, l'esprit de l'escalier, Loebner Prize, Menlo Park, Ray Kurzweil, RFID, Richard Feynman, Richard Feynman, Ronald Reagan, Skype, statistical model, Stephen Hawking, Steve Jobs, Steven Pinker, theory of mind, Thomas Bayes, Turing machine, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!, zero-sum game

“I’m a mule,” says the steelworker. “A monkey can do what I do,” says the receptionist. “I’m less than a farm implement,” says the migrant worker. “I’m an object,” says the high-fashion model. Blue collar and white call upon the identical phrase: “I’m a robot.” –STUDS TERKEL The notion of computer therapists of course raises one of the major things that people think of when AI comes to mind: losing their jobs. Automation and mechanization have been reshaping the job market for several centuries at this point, and whether these changes have been positive or negative is a contentious issue. One side argues that machines take human jobs away; the other side argues that increased mechanization has resulted in economic efficiency that raises the standard of living for all, and that has released humans from a number of unpleasant tasks.


pages: 378 words: 110,518

Postcapitalism: A Guide to Our Future by Paul Mason

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Alfred Russel Wallace, bank run, banking crisis, banks create money, Basel III, basic income, Bernie Madoff, Bill Gates: Altair 8800, bitcoin, Branko Milanovic, Bretton Woods, BRICs, British Empire, business process, butterfly effect, call centre, capital controls, Cesare Marchetti: Marchetti’s constant, Claude Shannon: information theory, collaborative economy, collective bargaining, Corn Laws, corporate social responsibility, creative destruction, credit crunch, currency manipulation / currency intervention, currency peg, David Graeber, deglobalization, deindustrialization, deskilling, discovery of the americas, Downton Abbey, drone strike, en.wikipedia.org, energy security, eurozone crisis, factory automation, financial repression, Firefox, Fractional reserve banking, Frederick Winslow Taylor, full employment, future of work, game design, income inequality, inflation targeting, informal economy, information asymmetry, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kenneth Arrow, Kevin Kelly, knowledge economy, knowledge worker, late capitalism, low skilled workers, market clearing, means of production, Metcalfe's law, money: store of value / unit of account / medium of exchange, mortgage debt, Network effects, new economy, Norbert Wiener, Occupy movement, oil shale / tar sands, oil shock, Paul Samuelson, payday loans, Pearl River Delta, post-industrial society, precariat, price mechanism, profit motive, quantitative easing, race to the bottom, RAND corporation, rent-seeking, reserve currency, RFID, Richard Stallman, Robert Gordon, Robert Metcalfe, secular stagnation, sharing economy, Stewart Brand, structural adjustment programs, supply-chain management, The Future of Employment, the scientific method, The Wealth of Nations by Adam Smith, Transnistria, union organizing, universal basic income, urban decay, urban planning, Vilfredo Pareto, wages for housework, women in the workforce

In 2014, the OECD released its projections for the world economy in the years between now and 2060.40 World growth will slow to 2.7 per cent, said the Paris-based think tank, because the catch-up effects boosting growth in the developing world – growing population, education, urbanization – will peter out. Even before that, near-stagnation in advanced economies indicates average global growth of just 3 per cent over the next fifty years, significantly below the pre-crisis average. Meanwhile, because semi-skilled jobs will become automated, leaving only high- and low-paid ones, global inequality will rise by 40 per cent. By 2060, countries such as Sweden will have the levels of inequality currently seen in the USA: think Gary, Indiana in the suburbs of Stockholm. There is also the very real risk that climate change will begin to destroy capital, coastal land and agriculture, shaving up to 2.5 per cent off world GDP, and 6 per cent in south-east Asia.

The 250-year history of capitalism has been about pushing market forces into sectors where they did not exist before. Info-capitalism would have to take this to its extremes, creating new forms of person-to-person micro-services, paid for using micro-payments, and mainly in the private sector. And finally, for info-capitalism to succeed it would have to find work for the millions of people whose jobs are automated. These could not be in the majority low-paid jobs because the traditional escape mechanism needs labour costs to rise: human life has to become more complex, needing more labour inputs, not fewer, as in the four cyclical upswings described by long-cycle theory. If all these things could happen, info-capitalism could take off. The elements of such a solution are there in modern economies: Apple is the classic price monopolist, Amazon’s business model the classic strategy for capturing externalities; commodity speculation the classic driver of energy and raw material costs above their value; while the rise of personal micro-services – dog minding, nail salons, personal concierges and the like – shows capitalism commercializing activities we used to provide through friendship or informality.

They predicted two waves of computerization over the next twenty years: ‘In the first wave, we find that most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labour in production occupations, are likely to be substituted by computer capital.’36 In the second wave, it is everything relying on finger dexterity, observation, feedback, or working in a cramped space that gets robotized. They concluded the jobs safest from automation were service jobs where a high understanding of human interaction was needed – for example, nursing – and jobs requiring creativity. The study provoked an outcry along familiar under-consumptionist lines: robots will kill capitalism because they will create mass underemployment and consumption will collapse. That is a real danger. To overcome it, capitalism would have to greatly expand the human services sector.


pages: 371 words: 108,317

The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future by Kevin Kelly

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3D printing, A Declaration of the Independence of Cyberspace, AI winter, Airbnb, Albert Einstein, Amazon Web Services, augmented reality, bank run, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, book scanning, Brewster Kahle, Burning Man, cloud computing, commoditize, computer age, connected car, crowdsourcing, dark matter, dematerialisation, Downton Abbey, Edward Snowden, Elon Musk, Filter Bubble, Freestyle chess, game design, Google Glasses, hive mind, Howard Rheingold, index card, indoor plumbing, industrial robot, Internet Archive, Internet of things, invention of movable type, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Kickstarter, lifelogging, linked data, Lyft, M-Pesa, Marc Andreessen, Marshall McLuhan, means of production, megacity, Minecraft, multi-sided market, natural language processing, Netflix Prize, Network effects, new economy, Nicholas Carr, old-boy network, peer-to-peer, peer-to-peer lending, personalized medicine, placebo effect, planetary scale, postindustrial economy, recommendation engine, RFID, ride hailing / ride sharing, Rodney Brooks, self-driving car, sharing economy, Silicon Valley, slashdot, Snapchat, social graph, social web, software is eating the world, speech recognition, Stephen Hawking, Steven Levy, Ted Nelson, the scientific method, transport as a service, two-sided market, Uber for X, Watson beat the top human players on Jeopardy!, Whole Earth Review, zero-sum game

The machine translator does Turkish to Hindi, or French to Korean, etc. It can of course translate any text. High-level diplomatic translators won’t lose their jobs for a while, but day-to-day translating chores in business will all be better done by machines. In fact, any job dealing with reams of paperwork will be taken over by bots, including much of medicine. The rote tasks of any information-intensive job can be automated. It doesn’t matter if you are a doctor, translator, editor, lawyer, architect, reporter, or even programmer: The robot takeover will be epic. We are already at the inflection point. We have preconceptions about how an intelligent robot should look and act, and these can blind us to what is already happening around us. To demand that artificial intelligence be humanlike is the same flawed logic as demanding that artificial flying be birdlike, with flapping wings.

One hundred years ago not a single citizen of China would have told you that they would rather buy a tiny glassy slab that allowed them to talk to faraway friends before they would buy indoor plumbing. But every day peasant farmers in China without plumbing purchase smartphones. Crafty AIs embedded in first-person shooter games have given millions of teenage boys the urge, the need, to become professional game designers—a dream that no boy in Victorian times ever had. In a very real way our inventions assign us our jobs. Each successful bit of automation generates new occupations—occupations we would not have fantasized about without the prompting of the automation. To reiterate, the bulk of new tasks created by automation are tasks only other automation can handle. Now that we have search engines like Google, we set the servant upon a thousand new errands. Google, can you tell me where my phone is? Google, can you match the people suffering depression with the doctors selling pills?

See also artificial intelligence “machine readable” information, 267 Magic Leap, 216 malaria, 241 Malthus, Thomas, 243 Mann, Steve, 247 Manovich, Lev, 200 manufacturing, robots in, 52–53, 55 maps, 272 mathematics, 47, 239, 242–43 The Matrix (1999), 211 maximum likelihood estimation (MLE), 265 McDonalds, 25–26 McLuhan, Marshall, 63, 127 media fluency, 201 media genres, 194–95 medical technology and field AI applications in, 31, 55 and crowdfunding, 157 and diagnoses, 31 future flows of, 80 interpretation services in field of, 69 and lifelogging, 250 new jobs related to automation in, 58 paperwork in, 51 personalization of, 69 and personalized pharmaceuticals, 173 and pooling patient data, 145 and tracking technology, 173, 237, 238–40, 241–42, 243–44, 250 Meerkat, 76 memory, 245–46, 249 messaging, 239–40 metadata, 258–59, 267 microphones, 221 Microsoft, 122–23, 124, 216, 247 minds, variety of, 44–46 Minecraft, 218 miniaturization, 237 Minority Report (2002), 221–22, 255 MIT Media Lab, 219, 220, 222 money, 4, 65, 119–21 monopolies, 209 mood tracking, 238 Moore’s Law, 257 movies, 77–78, 81–82, 168, 204–7 Mozilla, 151 MP3 compression, 165–66 music and musicians AI applications in, 35 creation of, 73–76, 77 and crowdfunding, 157 and free/ubiquitous copies, 66–67 and intellectual property issues, 208–9 and interactivity, 221 liquidity of, 66–67, 73–78 and live performances, 71 low-cost reproduction of, 87 of nonprofessionals, 75–76 and patronage, 72 sales of, 75 soundtracks for content, 76 total volume of recorded music, 165–66 Musk, Elon, 44 mutual surveillance (“coveillance”), 259–64 MyLifeBits, 247 Nabokov, Vladimir, 204 Napster, 66 The Narrative, 248–49, 251 National Geographic, 278 National Science Foundation, 17–18 National Security Agency (NSA), 261 Nature, 32 Negroponte, Nicholas, 16, 219 Nelson, Ted, 18–19, 21, 247 Nest smart thermostat, 253, 283 Netflix and accessibility vs. ownership, 109 and crowdsourcing programming, 160 and on-demand access, 64 and recommendation engines, 39, 154, 169 and reviews, 73, 154 and sharing economy, 138 and tracking technology, 254 Netscape browser, 15 network effect, 40 neural networks, 38–40 newbies, 10–11, 15 new media forms, 194–95 newspapers, 177 Ng, Andrew, 38, 39 niche interests, 155–56 nicknames, 263 nondestructive editing, 206 nonprofits, 157 noosphere, 292 Northwestern University, 225 numeracy, 242–43 Nupedia, 270 OBD chips, 251, 252 obscure or niche interests, 155–56 office settings, 222.


pages: 361 words: 81,068

The Internet Is Not the Answer by Andrew Keen

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3D printing, A Declaration of the Independence of Cyberspace, Airbnb, AltaVista, Andrew Keen, augmented reality, Bay Area Rapid Transit, Berlin Wall, bitcoin, Black Swan, Bob Geldof, Burning Man, Cass Sunstein, citizen journalism, Clayton Christensen, clean water, cloud computing, collective bargaining, Colonization of Mars, computer age, connected car, creative destruction, cuban missile crisis, David Brooks, disintermediation, Donald Davies, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, Frank Gehry, Frederick Winslow Taylor, frictionless, full employment, future of work, gig economy, global village, Google bus, Google Glasses, Hacker Ethic, happiness index / gross national happiness, income inequality, index card, informal economy, information trail, Innovator's Dilemma, Internet of things, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Julian Assange, Kevin Kelly, Kickstarter, Kodak vs Instagram, Lean Startup, libertarian paternalism, lifelogging, Lyft, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Metcalfe’s law, move fast and break things, move fast and break things, Nate Silver, Network effects, new economy, Nicholas Carr, nonsequential writing, Norbert Wiener, Norman Mailer, Occupy movement, packet switching, PageRank, Paul Graham, peer-to-peer, peer-to-peer rental, Peter Thiel, Plutocrats, plutocrats, Potemkin village, precariat, pre–internet, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, Robert Metcalfe, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Skype, smart cities, Snapchat, social web, South of Market, San Francisco, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, TaskRabbit, Ted Nelson, telemarketer, The Future of Employment, the medium is the message, the new new thing, Thomas L Friedman, Tyler Cowen: Great Stagnation, Uber for X, urban planning, Vannevar Bush, Whole Earth Catalog, WikiLeaks, winner-take-all economy, working poor, Y Combinator

And, everyone’s favorite, ROBOTS,” wrote the Atlantic’s Derek Thompson in 2014 about our increasing concern with the elimination of jobs from the economy.17 As if to mark (or perhaps mourn) the twenty-fifth anniversary of the Web, it seems as if 2014 is the year that we’ve finally fully woken up to what the Wall Street Journal columnist Daniel Akst dubs “automation anxiety.”18 The cover of the one business magazine that I’d read on the flight from Chicago to Rochester, for example, featured the image of a deadly tornado roaring through a workspace. “Coming to an office near you . . .,” it warned about what technology will do to “tomorrow’s jobs.”19 Many others share this automation anxiety. The distinguished Financial Times economics columnist Martin Wolf warns that intelligent machines could hollow out middle-class jobs, compound income inequality, make the wealthy “indifferent” to the fate of everyone else, and make a “mockery” of democratic citizenship.20 “The robots are coming and will terminate your jobs,”21 worries the generally cheerful economist Tim Harford in response to Google’s acquisition in December 2013 of Boston Dynamics, a producer of military robots such as Big Dog, a three-foot-long, 240-pound, four-footed beast that can carry a 340-pound load and climb snowy hiking trails.

Citing a paper by Oxford University’s Carl Benedikt Frey and Michael Osborne that predicts that 47% of all American jobs might be lost in the next couple of decades,40 the Atlantic’s Derek Thompson speculates on “which half” of the workforce could be made redundant by robots. Of the ten jobs that have a 99% likelihood of being replaced by networked software and automation over the next quarter century, Thompson includes tax preparers, library technicians, telemarketers, sewers in clothing factories, accounts clerks, and photographic process workers.41 While it’s all very well to speculate about who will lose their jobs because of automation, Thompson says, “the truth is scarier. We don’t have a clue.”42 But Thompson is wrong. The writing is on the wall about both the winners and the losers in this dehumanizing race between computers and people. We do indeed have more than a clue about its outcome. And that’s what really is scary. The Writing on the Wall Not everything about our automation anxiety is speculative. Indeed, when it comes to photographic process workers, there’s a 100% certainty that they lost the race with computers for jobs.


pages: 187 words: 55,801

The New Division of Labor: How Computers Are Creating the Next Job Market by Frank Levy, Richard J. Murnane

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Atul Gawande, call centre, computer age, Computer Numeric Control, correlation does not imply causation, David Ricardo: comparative advantage, deskilling, Frank Levy and Richard Murnane: The New Division of Labor, Gunnar Myrdal, hypertext link, index card, information asymmetry, job automation, knowledge economy, knowledge worker, low skilled workers, low-wage service sector, pattern recognition, profit motive, Robert Shiller, Robert Shiller, Ronald Reagan, speech recognition, talking drums, telemarketer, The Wealth of Nations by Adam Smith, working poor

The unemployment rate moved through recessions and expansions but the same jobs that were lost on downturns were largely replaced on the upturns. Because the job market was fairly stable, the policies that interacted with the job market—the tax system, education, training—could be stable as well. That world is largely gone now. Many of the jobs lost in the post-2000 recession—clerical and factory jobs lost to automation, call center jobs lost to India, manufacturing jobs lost to China—will not be coming back. This dynamic environment requires new policies and the first step in creating new policies is to recognize our new situation. In chapter 1, we listed a set of four questions this book was designed to answer: • What kinds of tasks do humans perform better than computers? • What kinds of tasks do computers perform better than humans?


pages: 293 words: 81,183

pages: 49 words: 12,968

Industrial Internet by Jon Bruner

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autonomous vehicles, barriers to entry, commoditize, computer vision, data acquisition, demand response, en.wikipedia.org, factory automation, Google X / Alphabet X, industrial robot, Internet of things, job automation, loose coupling, natural language processing, performance metric, Silicon Valley, slashdot, smart grid, smart meter, statistical model, web application

If information is seamlessly captured from machines as well as people, we’ll need fewer low-level data shepherds like medical transcriptionists (ironically, the demand for these types of jobs has increased with the introduction of electronic medical records, though that’s largely due to the persistence of poor user interfaces and interoperability barriers). The industrial internet will automate certain repetitive jobs that have so far resisted automation because they require some degree of human judgment and spatial understanding — driving a truck, perhaps, or recognizing a marred paint job on an assembly line. In fast-growing fields like health care, displaced workers might be absorbed into other low- or medium-skill roles, but in others, the economic tradeoffs will be similar to those in factory automation: higher productivity, lower prices for consumers, continued feasibility of manufacturing in high-cost countries like the United States — but also fewer jobs for people without high-demand technical skills.


pages: 181 words: 52,147

The Driver in the Driverless Car: How Our Technology Choices Will Create the Future by Vivek Wadhwa, Alex Salkever

23andMe, 3D printing, Airbnb, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, Bernie Sanders, bitcoin, blockchain, clean water, correlation does not imply causation, distributed ledger, Donald Trump, double helix, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Google bus, Hyperloop, income inequality, Internet of things, job automation, Kevin Kelly, Khan Academy, Law of Accelerating Returns, license plate recognition, life extension, Lyft, M-Pesa, Menlo Park, microbiome, mobile money, new economy, personalized medicine, phenotype, precision agriculture, RAND corporation, Ray Kurzweil, recommendation engine, Ronald Reagan, Second Machine Age, self-driving car, Silicon Valley, Skype, smart grid, stem cell, Stephen Hawking, Steve Wozniak, Stuxnet, supercomputer in your pocket, Tesla Model S, The Future of Employment, Turing test, Uber and Lyft, Uber for X, uranium enrichment, Watson beat the top human players on Jeopardy!, zero day

Famed venture capitalist Vinod Khosla estimates that technology will replace 80 percent of doctors.3 But similar job losses face those in practically every profession that necessitates a human’s judgment or light creative problem solving. A.I.’s medical judgments are already superseding those of human physicians.4 Another example of a profession that you might not expect to be at risk is the legal profession. Only a few decades ago, a law degree was considered a ticket to a solid middle-or upper-middle-class life in the United States. Today, young lawyers are struggling to find jobs, and salaries are stagnant. Automation driven by A.I. has begun to rapidly strip away chunks of what junior attorneys formerly used to do, from contract analysis to document discovery. Symantec, for example, has a software product, Clearwell, that does legal discovery. Legal discovery is the laborious process of sifting through boxes of documents, reams of e-mails, and numerous other forms of information submitted to the court by litigants.

Rather, the robots will replace humans piecemeal in performing tasks, through specializations. In this fashion, the robots will gradually, task by task, assume the jobs of humans in manufacturing plants, in grocery stores, in pharmacies. Hospitals rely on A.I.-driven systems in their pharmacies right now to spot potential problems due to conflicting medicines. I can envisage the job of pharmacist being completely automated. Further down the economic food chain, McDonald’s is in the process of rolling out automated order-taking at its counters. This could be matched by an automated engine to cook hamburger and fries. One of these already exists. It’s from a venture-backed company called Momentum Machines and can make a hamburger every ten seconds. That may sound ominous; yes, robots may eat our jobs.

However, today’s technologies could automate 45 percent of the activities people are paid to perform across all occupations. What’s more, about 60 percent of all occupations could see 30 percent or more of their work activities automated.”11 The report also notes that the mere ability to automate work doesn’t make it a sensible thing to do. As long as $10-per-hour cooks are cheaper than Momentum Machines on fast-food lines, it’s unlikely that food-service jobs will succumb to automation. The alternative extreme—no robots—is simply not realistic. The giant bubble of aging people could overwhelm most of the developed world, as well as many developing countries, such as China. Self-driving cars will save tens of millions of lives over the next decades. More agile and intelligent robots will take over the most dangerous human tasks and jobs such as mining, firefighting, search and rescue, and inspecting tall buildings and communications towers.


pages: 440 words: 108,137

The Meritocracy Myth by Stephen J. McNamee

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affirmative action, Affordable Care Act / Obamacare, Bernie Madoff, British Empire, collective bargaining, computer age, conceptual framework, corporate governance, deindustrialization, delayed gratification, demographic transition, desegregation, deskilling, equal pay for equal work, estate planning, failed state, fixed income, gender pay gap, Gini coefficient, glass ceiling, helicopter parent, income inequality, informal economy, invisible hand, job automation, joint-stock company, labor-force participation, low-wage service sector, marginal employment, Mark Zuckerberg, mortgage debt, mortgage tax deduction, new economy, New Urbanism, obamacare, occupational segregation, old-boy network, pink-collar, Plutocrats, plutocrats, Ponzi scheme, post-industrial society, prediction markets, profit motive, race to the bottom, random walk, school choice, Scientific racism, Steve Jobs, The Bell Curve by Richard Herrnstein and Charles Murray, The Spirit Level, The Wealth of Nations by Adam Smith, too big to fail, trickle-down economics, upwardly mobile, We are the 99%, white flight, young professional

While computerization created some new jobs with high skill requirements, other jobs have been automated or “deskilled” by computerization. Sales clerks, for instance, no longer need to calculate change. In fast-food chains, keyboards on cash registers sometimes display pictures rather than numbers. By the beginning of the twenty-first century, even computer-programming jobs, the supposed leading edge of the postindustrial boom, experienced sharp job losses. Between 2000 and 2004, 180,000 computer-programming jobs, or about one-quarter of the occupation’s total employment, were lost (Hacker 2008, 77). These jobs fell victim to two trends adversely affecting many other sectors of the labor force: automation and outsourcing. Many routine programming jobs were automated as advanced “canned” software programs were developed, eliminating the need to write programs in more complex and labor-intensive BASIC code.


pages: 441 words: 136,954

That Used to Be Us by Thomas L. Friedman, Michael Mandelbaum

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3D printing, Affordable Care Act / Obamacare, Albert Einstein, Amazon Web Services, American Society of Civil Engineers: Report Card, Andy Kessler, Ayatollah Khomeini, bank run, barriers to entry, Berlin Wall, blue-collar work, Bretton Woods, business process, call centre, carbon footprint, Carmen Reinhart, Cass Sunstein, centre right, Climatic Research Unit, cloud computing, collective bargaining, corporate social responsibility, creative destruction, Credit Default Swap, crowdsourcing, delayed gratification, energy security, Fall of the Berlin Wall, fear of failure, full employment, Google Earth, illegal immigration, immigration reform, income inequality, Intergovernmental Panel on Climate Change (IPCC), job automation, Kenneth Rogoff, knowledge economy, Lean Startup, low skilled workers, Mark Zuckerberg, market design, mass immigration, more computing power than Apollo, Network effects, obamacare, oil shock, pension reform, Report Card for America’s Infrastructure, rising living standards, Ronald Reagan, Rosa Parks, Saturday Night Live, shareholder value, Silicon Valley, Silicon Valley startup, Skype, Steve Jobs, the scientific method, Thomas L Friedman, too big to fail, University of East Anglia, WikiLeaks

Throughout the post–World War II period, until 1991, “it typically took on average eight months for jobs that were lost at the trough of a recession to come back to the old peak,” said Rajan. But with the introduction of all these new technologies and networks over the last two decades, that is no longer the case. With each recession and with each new hyper-flattening and hyper-connecting of the global marketplace, more and more jobs are being automated, digitized, or outsourced. “Look at the last three recessions,” said Rajan. “After 1991, it took twenty-three months for the jobs to come back to prerecession levels. After 2001, it took thirty-eight months. And after 2007, it is expected to take up to five years or more.” A key reason is that in the old cyclical recovery people got laid off and were rather quickly hired back into the workforce once demand rose again.

… Consider, for example, that half of Grinnell’s applicants from China this year have perfect scores of 800 on the math portion of the SAT, making the performance of one largely indistinguishable from another.” This is just one small reason that whatever your “extra” is—inventing a new product, reinventing an old product, or reinventing yourself to do a routine task in a new and better way—you need to fine-tune it, hone and promote it, to become a creative creator or creative server and keep your job from being outsourced, automated, digitized, or treated as an interchangeable commodity. Everyone’s “extra” can and will be different. For some it literally will be starting a company to make people’s lives more comfortable, educated, entertained, productive, healthy, or secure. And the good news is that in the hyper-connected world, that has never been easier. If you have just the spark of a new idea today, you can get a company in Taiwan to design it; you can get Alibaba in China to find you a low-cost Chinese manufacturer to make it; you can get Amazon.com to do your delivery and fulfillment and provide technology services from its cloud; you can find a bookkeeper on Craigslist to do your accounting and an artist on Freelancer.com to do your logo.

No one has more bluntly summed up why average is over, and what it means for education, than John Jazwiec, who has headed a variety of technology start-ups, including RedPrairie and FiveCubits. Blogging on his website, JohnJazwiec.com, he confessed: I am in the business of killing jobs. I kill jobs in three ways. I kill jobs when I sell, I kill jobs by killing competitors, and I kill jobs by focusing on internal productivity. All of the companies I have been a CEO of, through best-in-practice services and software, eliminate jobs. They eliminate jobs by automation, outsourcing, and efficiencies of process. The marketing is clear—less workers, more consistent output. I reckon in the last decade I have eliminated over 100,000 jobs in the worldwide economy from the software and services my companies sell. I know the number, because … my revenues … are based on the number of jobs I kill. I have killed many competitors. Again, I reckon I have eliminated over 100,000 jobs in the last decade.


pages: 410 words: 119,823

Radical Technologies: The Design of Everyday Life by Adam Greenfield

3D printing, Airbnb, augmented reality, autonomous vehicles, bank run, barriers to entry, basic income, bitcoin, blockchain, business intelligence, business process, call centre, cellular automata, centralized clearinghouse, centre right, Chuck Templeton: OpenTable, cloud computing, collective bargaining, combinatorial explosion, Computer Numeric Control, computer vision, Conway's Game of Life, cryptocurrency, David Graeber, dematerialisation, digital map, distributed ledger, drone strike, Elon Musk, ethereum blockchain, facts on the ground, fiat currency, global supply chain, global village, Google Glasses, IBM and the Holocaust, industrial robot, informal economy, information retrieval, Internet of things, James Watt: steam engine, Jane Jacobs, Jeff Bezos, job automation, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, joint-stock company, Kevin Kelly, Kickstarter, late capitalism, license plate recognition, lifelogging, M-Pesa, Mark Zuckerberg, means of production, megacity, megastructure, minimum viable product, money: store of value / unit of account / medium of exchange, natural language processing, Network effects, New Urbanism, Occupy movement, Oculus Rift, Pareto efficiency, pattern recognition, Pearl River Delta, performance metric, Peter Eisenman, Peter Thiel, planetary scale, Ponzi scheme, post scarcity, RAND corporation, recommendation engine, RFID, rolodex, Satoshi Nakamoto, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, smart cities, smart contracts, sorting algorithm, special economic zone, speech recognition, stakhanovite, statistical model, stem cell, technoutopianism, Tesla Model S, the built environment, The Death and Life of Great American Cities, The Future of Employment, transaction costs, Uber for X, universal basic income, urban planning, urban sprawl, Whole Earth Review, WikiLeaks, women in the workforce

The great twentieth-century economist John Maynard Keynes had foreseen much of this early on, coining the expression “technological unemployment” sometime around 1928.1 He saw, with almost clairvoyant perspicacity, that societies might eventually automate away the jobs much of their labor force depended on, and his insight is borne out in recent United States government estimates that an American worker making less than $20 an hour now has an 83 percent chance of losing their job to automation.2 But what Keynes concluded—that the eclipse of human labor by technical systems would necessarily compel a turn toward a full-leisure society—has not come to pass, not even remotely. And what neither Keynes nor any other economist reckoned with, until very recently, was the thought that the process of automation would hardly stop when it had replaced manual and clerical labor. If automation was initially brought to bear on tasks that were one or more of the “four Ds”—dull, dirty, difficult or dangerous—the advent of sophisticated machine-learning algorithms means that professional and managerial work now comes into range.

Osborne of the University of Oxford found that 47 percent of them were vulnerable to near-term advances in machine learning and mobile robotics.23 Among developing countries, this rises to 69 percent in India, 77 percent in China and an astonishing 85 percent in Ethiopia.24 (Again, these figures refer to the percentage of job categories that are susceptible to replacement, not of workers in employment.) Meanwhile, against the oft-cited hope that technology would generate more jobs than it eliminated, Frey found that fewer than 0.5 percent of the US workforce have found employment in the high-technology industries that have emerged since the turn of the century. A World Economic Forum estimate that some five million jobs would be lost to automation by 2020 has to be regarded as a stark outlier, if not a gross error, especially since Bank of England Chief Economist Andy Haldane reckons that 15 million jobs would disappear over the same timeframe in the United Kingdom alone.25 I’m not qualified to discuss, in any but the broadest terms, what will happen to the shape and structure of national economies in the aftermath of pervasive automation.


pages: 590 words: 153,208

Wealth and Poverty: A New Edition for the Twenty-First Century by George Gilder

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affirmative action, Albert Einstein, Bernie Madoff, British Empire, capital controls, cleantech, cloud computing, collateralized debt obligation, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, deindustrialization, diversified portfolio, Donald Trump, equal pay for equal work, floating exchange rates, full employment, George Gilder, Gunnar Myrdal, Home mortgage interest deduction, Howard Zinn, income inequality, invisible hand, Jane Jacobs, Jeff Bezos, job automation, job-hopping, Joseph Schumpeter, knowledge economy, labor-force participation, margin call, Mark Zuckerberg, means of production, medical malpractice, minimum wage unemployment, money market fund, money: store of value / unit of account / medium of exchange, Mont Pelerin Society, moral hazard, mortgage debt, non-fiction novel, North Sea oil, paradox of thrift, Paul Samuelson, Plutocrats, plutocrats, Ponzi scheme, post-industrial society, price stability, Ralph Nader, rent control, Robert Gordon, Ronald Reagan, Silicon Valley, Simon Kuznets, skunkworks, Steve Jobs, The Wealth of Nations by Adam Smith, Thomas L Friedman, upwardly mobile, urban renewal, volatility arbitrage, War on Poverty, women in the workforce, working poor, working-age population, yield curve, zero-sum game

Because federal control and oversight requirements have been imposing large new burdens of medical paperwork, the automation of this aspect of health care tends to free nurses and doctors to concentrate on their real duties with patients. The average intern today, for example, spends perhaps 90 percent of his time on paperwork. It is the growth of human bureaucracy, with its necessary rules and reporting requirements, that creates alienating and impersonal jobs. Automation tends to enhance the administrators’ span of control and reduce the need for middle managers and clerks doing machine-like tasks. All such improvements do not depend on full automation. An example of the kind of small advances in management that can yield large gains in efficiency is the hot line for diabetics, which was pushed by Dr. Reese Alsop and by Dr. Peter Bourne before his departure from the White House.


pages: 391 words: 105,382

Utopia Is Creepy: And Other Provocations by Nicholas Carr

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Air France Flight 447, Airbnb, Airbus A320, AltaVista, Amazon Mechanical Turk, augmented reality, autonomous vehicles, Bernie Sanders, book scanning, Brewster Kahle, Buckminster Fuller, Burning Man, Captain Sullenberger Hudson, centralized clearinghouse, cloud computing, cognitive bias, collaborative consumption, computer age, corporate governance, crowdsourcing, Danny Hillis, deskilling, digital map, Donald Trump, Electric Kool-Aid Acid Test, Elon Musk, factory automation, failed state, feminist movement, Frederick Winslow Taylor, friendly fire, game design, global village, Google bus, Google Glasses, Google X / Alphabet X, Googley, hive mind, impulse control, indoor plumbing, interchangeable parts, Internet Archive, invention of movable type, invention of the steam engine, invisible hand, Isaac Newton, Jeff Bezos, jimmy wales, job automation, Kevin Kelly, lifelogging, low skilled workers, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, Menlo Park, mental accounting, natural language processing, Network effects, new economy, Nicholas Carr, Norman Mailer, off grid, oil shale / tar sands, Peter Thiel, Plutocrats, plutocrats, profit motive, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, Republic of Letters, robot derives from the Czech word robota Czech, meaning slave, Ronald Reagan, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley ideology, Singularitarianism, Snapchat, social graph, social web, speech recognition, Startup school, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, technoutopianism, the medium is the message, theory of mind, Turing test, Whole Earth Catalog, Y Combinator

Even Adam Smith understood that machinery, in enhancing labor productivity, would often end up narrowing jobs, turning skilled work into routine work. At worst, he wrote, the factory worker would become “as stupid and ignorant as it is possible for a human creature to become.” That’s not the whole picture, of course. In evaluating the long-term effects of automation, we have to look beyond particular job categories. Even as automation reduces the skill requirements of an established occupation, it may contribute to the creation of large new categories of interesting and well-paid work. That’s what happened, as the endless-ladder mythologists like to remind us, during the latter stages of the industrial revolution. The efficiencies of assembly lines and other mechanized forms of production pushed down the prices of all sorts of goods, which drove up demand for those goods, which led manufacturers to hire not only lots of blue-collar workers to operate and repair the machines but also lots of white-collar workers to manage the factories, design new products, market and sell the goods, keep the books, and so forth.


pages: 147 words: 45,890

Aftershock: The Next Economy and America's Future by Robert B. Reich

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Berlin Wall, declining real wages, delayed gratification, Doha Development Round, endowment effect, full employment, George Akerlof, Home mortgage interest deduction, Hyman Minsky, illegal immigration, income inequality, invisible hand, job automation, labor-force participation, Long Term Capital Management, loss aversion, mortgage debt, new economy, offshore financial centre, Ralph Nader, Ronald Reagan, school vouchers, sovereign wealth fund, Thorstein Veblen, too big to fail, World Values Survey

“This factory marks a … major … millstone, er, milestone.” I congratulated the governor and got out of there as fast as I could. Remember bank tellers? Telephone operators? The fleets of airline workers behind counters who issued tickets? Service-station attendants? These and millions of other jobs weren’t lost to globalization; they were lost to automation. America has lost at least as many jobs to automated technology as it has to trade. Any routine job that requires the same steps to be performed over and over can potentially be done anywhere in the world by someone working for far less than an American wage, or it can be done by automated technology. By the late 1970s, all such jobs were on the endangered species list. By 2010, they were nearly extinct. But contrary to popular mythology, trade and technology have not really reduced the number of jobs available to Americans.


pages: 202 words: 59,883

Age of Context: Mobile, Sensors, Data and the Future of Privacy by Robert Scoble, Shel Israel

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Albert Einstein, Apple II, augmented reality, call centre, Chelsea Manning, cloud computing, connected car, Edward Snowden, Edward Thorp, Elon Musk, factory automation, Filter Bubble, Google Earth, Google Glasses, Internet of things, job automation, John Markoff, Kickstarter, lifelogging, Marc Andreessen, Mars Rover, Menlo Park, Metcalfe’s law, New Urbanism, PageRank, pattern recognition, RFID, ride hailing / ride sharing, Robert Metcalfe, Saturday Night Live, self-driving car, sensor fusion, Silicon Valley, Skype, smart grid, social graph, speech recognition, Steve Jobs, Steve Wozniak, Steven Levy, Tesla Model S, Tim Cook: Apple, urban planning, Zipcar

Could such smart grids prevent such tragedies as the one caused by the massive forest fire that took the lives of 19 Arizona firefighters in June 2013? Perhaps not quite yet. But they are coming closer all the time. Robotic Household Assistants Another category of personal assistants for the home steps out of the pages of science fiction and perhaps meanders over the freaky line. Robots have long existed as characters in books and movies. More recently they have started taking over the most tedious jobs in automated factories and some of the most dangerous first-response work, such as disarming explosive devices. Now robots are finding roles in the home. In some cases they are serving as novelty possessions for the affluent in Asia. In India, robot maids are used by some of the country’s uppercrust. The Times of India, a favorite publication of the nation’s elite, alleged that it was because robots are less prone to tantrums than the humans they are replacing.


pages: 241 words: 43,073

pages: 209 words: 80,086

The Global Auction: The Broken Promises of Education, Jobs, and Incomes by Phillip Brown, Hugh Lauder, David Ashton

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active measures, affirmative action, barriers to entry, Branko Milanovic, BRICs, business process, business process outsourcing, call centre, collective bargaining, corporate governance, creative destruction, credit crunch, David Ricardo: comparative advantage, deindustrialization, deskilling, Frederick Winslow Taylor, full employment, future of work, glass ceiling, global supply chain, immigration reform, income inequality, industrial cluster, industrial robot, intangible asset, job automation, Joseph Schumpeter, knowledge economy, knowledge worker, labour market flexibility, low skilled workers, manufacturing employment, market bubble, market design, neoliberal agenda, new economy, Paul Samuelson, pensions crisis, post-industrial society, profit maximization, purchasing power parity, QWERTY keyboard, race to the bottom, Richard Florida, Ronald Reagan, shareholder value, Silicon Valley, sovereign wealth fund, stem cell, The Bell Curve by Richard Herrnstein and Charles Murray, The Wealth of Nations by Adam Smith, Thomas L Friedman, trade liberalization, transaction costs, trickle-down economics, winner-take-all economy, working poor, zero-sum game

This is an issue to which we will return in the final chapter, but there is another argument popular with American economists embracing the view that income inequalities are a result of changes in technologies. Is There a Hi-Tech Elephant in the Room? The idea that income inequalities are explained by the introduction of new technologies rather than global trade is intuitively attractive. It asserts that as new technologies are introduced into the workplace, some jobs are automated while more skilled workers are required to exploit the productive potential of new technologies. Widening income inequalities reflect the growing disparity in productivity achieved by high- as opposed to low-skill employees. “It seems undeniable,” suggests Paul Krugman, a Nobel Prize winner, “that the increase in the skill premium in the advanced world is primarily the result of skillbiased technological change.”35 Other luminaries like Lawrence Summers reaffirmed this view, claiming that “most of the observed increases in income inequality in the American economy are due to new technology rather than increased trade,” although he does recognize the threat of the global auction.36 The idea that new technologies usually demand higher levels of skill has led economists to present education and technology as a race in which the supply of educated workers needs to keep up with technology-led demand; otherwise, a shortage of skilled workers will lead to a polarization of incomes.37 A major study by Claudia Goldin and Lawrence Katz documents how the supply of educated workers kept pace with demand for much of the twentieth century, which they called the century of human capital.


pages: 236 words: 67,953

Brave New World of Work by Ulrich Beck

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affirmative action, Asian financial crisis, basic income, Berlin Wall, collective bargaining, conceptual framework, Fall of the Berlin Wall, feminist movement, full employment, future of work, Gunnar Myrdal, hiring and firing, illegal immigration, income inequality, informal economy, job automation, knowledge worker, labour market flexibility, labour mobility, low skilled workers, McJob, means of production, mini-job, postnationalism / post nation state, profit maximization, purchasing power parity, rising living standards, Silicon Valley, working poor, working-age population, zero-sum game

Jeremy Rifkin has shown that in the United States the proportion of factory workers in the economically active population fell over the past thirty years from 33 per cent to 17 per cent, even though there was a sharp rise in industrial output.23 In ten years' time less than 12 per cent of America's working population will be employed in factories – and by the year 2020 the figure will be less than 2 per cent. Moreover, even in the classical service sectors where hopes are directed towards a new jobs miracle, automation and downsizing have long since begun. Those who boost the economy further will not only fail to overcome structural unemployment; they will actually reinforce it. For flourishing enterprises make their profits mainly through rationalization (and no one can be blamed for that in an economic system geared to profit). Why should they create jobs when machines can work much more efficiently than people?


pages: 364 words: 99,897

The Industries of the Future by Alec Ross

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23andMe, 3D printing, Airbnb, algorithmic trading, AltaVista, Anne Wojcicki, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, bioinformatics, bitcoin, blockchain, Brian Krebs, British Empire, business intelligence, call centre, carbon footprint, cloud computing, collaborative consumption, connected car, corporate governance, Credit Default Swap, cryptocurrency, David Brooks, disintermediation, Dissolution of the Soviet Union, distributed ledger, Edward Glaeser, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, fiat currency, future of work, global supply chain, Google X / Alphabet X, industrial robot, Internet of things, invention of the printing press, Jaron Lanier, Jeff Bezos, job automation, John Markoff, knowledge economy, knowledge worker, lifelogging, litecoin, M-Pesa, Marc Andreessen, Mark Zuckerberg, Mikhail Gorbachev, mobile money, money: store of value / unit of account / medium of exchange, new economy, offshore financial centre, open economy, Parag Khanna, peer-to-peer, peer-to-peer lending, personalized medicine, Peter Thiel, precision agriculture, pre–internet, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rubik’s Cube, Satoshi Nakamoto, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, social graph, software as a service, special economic zone, supply-chain management, supply-chain management software, technoutopianism, The Future of Employment, underbanked, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y Combinator, young professional

During the recent recession, one in twelve people working in sales in the United States was laid off. Two Oxford University professors who studied more than 700 detailed occupational types have published a study making the case that over half of US jobs could be at risk of computerization in the next two decades. Forty-seven percent of American jobs are at high risk for robot takeover, and another 19 percent face a medium level of risk. Those with jobs that are hard to automate—lawyers, for example—may be safe for now, but those with more easily automated white-collar jobs, like paralegals, are at high risk. In the greatest peril are the 60 percent of the US workforce whose main job function is to aggregate and apply information. When I was growing up, my mom worked as a paralegal at the Putnam County Courthouse in Winfield, West Virginia. Her job largely consisted of rummaging through enormous 15-pound books looking for specific information on old court cases and real estate closings.


pages: 509 words: 132,327

Rise of the Machines: A Cybernetic History by Thomas Rid

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1960s counterculture, A Declaration of the Independence of Cyberspace, agricultural Revolution, Albert Einstein, Alistair Cooke, Apple II, Apple's 1984 Super Bowl advert, back-to-the-land, Berlin Wall, British Empire, Brownian motion, Buckminster Fuller, business intelligence, Claude Shannon: information theory, conceptual framework, connected car, domain-specific language, Douglas Engelbart, Douglas Engelbart, dumpster diving, Extropian, full employment, game design, global village, Haight Ashbury, Howard Rheingold, Jaron Lanier, job automation, John Markoff, John von Neumann, Kevin Kelly, Marshall McLuhan, Menlo Park, Mother of all demos, new economy, New Journalism, Norbert Wiener, offshore financial centre, oil shale / tar sands, pattern recognition, RAND corporation, Silicon Valley, Simon Singh, speech recognition, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, technoutopianism, Telecommunications Act of 1996, telepresence, V2 rocket, Vernor Vinge, Whole Earth Catalog, Whole Earth Review, Y2K, Yom Kippur War, Zimmermann PGP

Unemployment in the United States steadily cycled upward throughout the 1950s, from 4.2 percent at the start of the decade to 5.8 percent.74 By the end of the decade, economists had begun articulating concerns about structural unemployment. But from 1961 to 1969, employment in the goods-producing industries grew by 19 percent, and the service sector grew by nearly 30 percent. It also became clear that computers and control systems created new jobs. A leading trade magazine, Automation, commissioned a study of 3,440 industrial plants. Eleven percent were using advanced automation technology, such as computer control. Of those automated factories, only 10.4 percent reported a reduction of personnel; 41.5 percent reported no change; and nearly half of all automated companies told the magazine that more workers were needed to service the machines, not fewer.75 The distinctly 1960s hype about automation had two main drivers.


pages: 448 words: 84,462

Testing Extreme Programming by Lisa Crispin, Tip House

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c2.com, continuous integration, data acquisition, database schema, Donner party, Drosophila, hypertext link, index card, job automation, web application

Why XP Teams Need Testers Much of the published material on Extreme Programming is aimed at programmers, customers, and managers. Some purists may argue that a tester role is unnecessary in XP projects: customers can write the acceptance tests and programmers can automate them. This can work, and certainly some successful XP projects don't have testers. We believe, however, that more XP teams can be successful by doing a better job of defining, automating, and running acceptance tests when someone is focused on that role and that this focus helps in other areas as well. If you don't like to think of someone in the tester "role" on an XP project (because the only true roles defined in XP are programmer and customer), think of having a programmer with a "tester focus." We'll illustrate this point with a true story about a remodeling project Lisa recently experienced, but first let's define what we mean by the term "tester."


pages: 413 words: 119,587

Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots by John Markoff

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A Declaration of the Independence of Cyberspace, AI winter, airport security, Apple II, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, basic income, Baxter: Rethink Robotics, Bill Duvall, bioinformatics, Brewster Kahle, Burning Man, call centre, cellular automata, Chris Urmson, Claude Shannon: information theory, Clayton Christensen, clean water, cloud computing, collective bargaining, computer age, computer vision, crowdsourcing, Danny Hillis, DARPA: Urban Challenge, data acquisition, Dean Kamen, deskilling, don't be evil, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, Dynabook, Edward Snowden, Elon Musk, Erik Brynjolfsson, factory automation, From Mathematics to the Technologies of Life and Death, future of work, Galaxy Zoo, Google Glasses, Google X / Alphabet X, Grace Hopper, Gunnar Myrdal, Gödel, Escher, Bach, Hacker Ethic, haute couture, hive mind, hypertext link, indoor plumbing, industrial robot, information retrieval, Internet Archive, Internet of things, invention of the wheel, Jacques de Vaucanson, Jaron Lanier, Jeff Bezos, job automation, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, knowledge worker, Kodak vs Instagram, labor-force participation, loose coupling, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, medical residency, Menlo Park, Mother of all demos, natural language processing, new economy, Norbert Wiener, PageRank, pattern recognition, pre–internet, RAND corporation, Ray Kurzweil, Richard Stallman, Robert Gordon, Rodney Brooks, Sand Hill Road, Second Machine Age, self-driving car, semantic web, shareholder value, side project, Silicon Valley, Silicon Valley startup, Singularitarianism, skunkworks, Skype, social software, speech recognition, stealth mode startup, Stephen Hawking, Steve Ballmer, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, strong AI, superintelligent machines, technological singularity, Ted Nelson, telemarketer, telepresence, telepresence robot, Tenerife airport disaster, The Coming Technological Singularity, the medium is the message, Thorstein Veblen, Turing test, Vannevar Bush, Vernor Vinge, Watson beat the top human players on Jeopardy!, Whole Earth Catalog, William Shockley: the traitorous eight, zero-sum game


pages: 504 words: 126,835

The Innovation Illusion: How So Little Is Created by So Many Working So Hard by Fredrik Erixon, Bjorn Weigel

Airbnb, Albert Einstein, asset allocation, autonomous vehicles, barriers to entry, Basel III, Bernie Madoff, bitcoin, Black Swan, blockchain, BRICs, Burning Man, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, Clayton Christensen, Colonization of Mars, commoditize, corporate governance, corporate social responsibility, creative destruction, crony capitalism, dark matter, David Graeber, David Ricardo: comparative advantage, discounted cash flows, distributed ledger, Donald Trump, Elon Musk, Erik Brynjolfsson, fear of failure, first square of the chessboard / second half of the chessboard, Francis Fukuyama: the end of history, George Gilder, global supply chain, global value chain, Google Glasses, Google X / Alphabet X, Gordon Gekko, high net worth, hiring and firing, Hyman Minsky, income inequality, income per capita, index fund, industrial robot, Internet of things, Jeff Bezos, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, joint-stock company, Joseph Schumpeter, Just-in-time delivery, Kevin Kelly, knowledge economy, labour market flexibility, laissez-faire capitalism, lump of labour, Lyft, manufacturing employment, Mark Zuckerberg, market design, Martin Wolf, mass affluent, means of production, Mont Pelerin Society, Network effects, new economy, offshore financial centre, pensions crisis, Peter Thiel, Potemkin village, price mechanism, principal–agent problem, Productivity paradox, QWERTY keyboard, RAND corporation, Ray Kurzweil, rent-seeking, risk tolerance, risk/return, Robert Gordon, Ronald Coase, Ronald Reagan, savings glut, Second Machine Age, secular stagnation, Silicon Valley, Silicon Valley startup, Skype, sovereign wealth fund, Steve Ballmer, Steve Jobs, Steve Wozniak, technological singularity, telemarketer, The Chicago School, The Future of Employment, The Nature of the Firm, The Wealth of Nations by Adam Smith, too big to fail, total factor productivity, transaction costs, transportation-network company, tulip mania, Tyler Cowen: Great Stagnation, University of East Anglia, unpaid internship, Vanguard fund, Yogi Berra

Potentially, it was argued, automation could destroy the industrial fabric of the United States and cause mass unemployment à la the Great Depression.12 However, the majority of these fears turned out to be unfounded – and, by the end of the decade, when the economy had improved and fears had abated, no one remembered what the panic had been about. Automation, like previous technological shifts, destroyed jobs, but it also created new ones, and much safer and better-paid jobs at that. An automation blitz never occurred; the process took several decades as technology had to adjust to the composition of markets, companies, and several other aspects than simply the capacity of machines to substitute for labor. Just as in the industrial revolution, automation did not win merely by showing up. It progressively improved and adjusted to the economic, social, and institutional conditions for innovation.

(i) Angry Birds (app game) (i) Anheuser-Busch (i) Ansoff, Igor (i) antitrust laws (i) anxiety and automation/high-tech employment (i), (ii) psychology of, and low growth expectations (i) Apollo, moon landing (i) Apple and Foxconn (i) iOS (i) iPad (i), (ii) iPhone (i), (ii), (iii), (iv), (v) iPod and value chains (i) and Nokia (i) unutilized cash balances (i) apps (i), (ii), (iii), (iv), (v), (vi), (vii) Arab Spring (2011) (i) Arendt, Hannah (i) Art Vandelay character (Seinfeld TV series) (i), (ii), (iii) artificial intelligence (AI) (i), (ii) see also automation; robotics/robots Asia Asian markets (i), (ii) labor market flexibility (i) regionalization of trade growth (i) see also East Asia Asian Tigers (Hong Kong, Singapore, South Korea, Taiwan) (i) Asimov, Isaac (i) aspirations (i), (ii), (iii), (iv), (v) asset bubbles (i) asset managers and financial regulation (i) and gray capitalism (i), (ii), (iii), (iv), (v), (vi) and modern portfolio theory (i) and retirement savings (i) AT&T, Bell Labs (i) automated teller machines (ATMs), and teller jobs (i) automation and labor (i), (ii), (iii), (iv), (v) see also artificial intelligence; New Machine Age thesis; robotics/robots; technology automobile industry see car industry “average is over” thesis (i) Babson College, entrepreneurship study (i) baby boomer (or boomer) generation (i), (ii), (iii), (iv) Back to the Future II (movie) (i) Bacon, Francis (i) Bailey, Ronald (i) Baldwin, Richard (i) Ballmer, Steve (i), (ii) ballooning (i) Balsillie, Jim (i) Bank for International Settlements (BIS) economists (i), (ii) banks bank services and globalization (i) bank teller jobs and ATMs (i) European banks and Basel III rules (i), (ii) and financial regulation (i), (ii) mobile banking in Africa (i) proneness to risk (i) “put option” (i) US banks and compliance officers (i) barber profession, evolution of (i) Basel III (i), (ii) BASF (i), (ii) Baumol, William (i), (ii), (iii), (iv)n70 “bazaar economy” (Hans-Werner Sinn) (i) Beals, Vaughn (i) Bean, Charles “Independent Review of UK Economic Statistics” (i) on UK productivity puzzle (i) Beer, Stafford (i), (ii) Being There (movie), Mr.


pages: 797 words: 227,399

Robotics Revolution and Conflict in the 21st Century by P. W. Singer

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agricultural Revolution, Albert Einstein, Any sufficiently advanced technology is indistinguishable from magic, Atahualpa, barriers to entry, Berlin Wall, Bill Joy: nanobots, blue-collar work, borderless world, clean water, Craig Reynolds: boids flock, cuban missile crisis, digital map, en.wikipedia.org, Ernest Rutherford, failed state, Fall of the Berlin Wall, Firefox, Francisco Pizarro, Frank Gehry, friendly fire, game design, George Gilder, Google Earth, Grace Hopper, I think there is a world market for maybe five computers, if you build it, they will come, illegal immigration, industrial robot, interchangeable parts, Intergovernmental Panel on Climate Change (IPCC), invention of gunpowder, invention of movable type, invention of the steam engine, Isaac Newton, Jacques de Vaucanson, job automation, Johann Wolfgang von Goethe, Law of Accelerating Returns, Mars Rover, Menlo Park, New Urbanism, pattern recognition, private military company, RAND corporation, Ray Kurzweil, RFID, robot derives from the Czech word robota Czech, meaning slave, Rodney Brooks, Ronald Reagan, Schrödinger's Cat, Silicon Valley, speech recognition, Stephen Hawking, strong AI, technological singularity, The Coming Technological Singularity, The Wisdom of Crowds, Turing test, Vernor Vinge, Wall-E, Yogi Berra

Here too automated systems are proving useful. One of the paradoxes of security screening at places like airports and railroad stations, for example, is that it is incredibly important, but also mind-numbingly boring. So, oddly, we have this most crucial job in countering terrorists performed by workers with little training, who are paid barely over minimum wage. As with other dull, dangerous, and dirty jobs, automated systems are coming into favor as a potential solution. Screening is beginning to be streamlined via such technologies as high-frequency radio scanners, which can automatically spot concealed weapons. Reminding many of the technology imagined in movies like Arnold Schwarzenegger’s 1990 flick Total Recall, the real-world version is a sort of automatic X-ray scan. It detects the radio waves that reflect off every material and automatically searches a person’s body or luggage for any incriminating objects.


pages: 588 words: 131,025

The Patient Will See You Now: The Future of Medicine Is in Your Hands by Eric Topol

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23andMe, 3D printing, Affordable Care Act / Obamacare, Anne Wojcicki, Atul Gawande, augmented reality, bioinformatics, call centre, Clayton Christensen, clean water, cloud computing, commoditize, computer vision, conceptual framework, connected car, correlation does not imply causation, creative destruction, crowdsourcing, dark matter, data acquisition, disintermediation, don't be evil, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Firefox, global village, Google Glasses, Google X / Alphabet X, Ignaz Semmelweis: hand washing, information asymmetry, interchangeable parts, Internet of things, Isaac Newton, job automation, Joseph Schumpeter, Julian Assange, Kevin Kelly, license plate recognition, lifelogging, Lyft, Mark Zuckerberg, Marshall McLuhan, meta analysis, meta-analysis, microbiome, Nate Silver, natural language processing, Network effects, Nicholas Carr, obamacare, pattern recognition, personalized medicine, phenotype, placebo effect, RAND corporation, randomized controlled trial, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, Snapchat, social graph, speech recognition, stealth mode startup, Steve Jobs, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Turing test, Uber for X, Watson beat the top human players on Jeopardy!, X Prize

We’ve already seen some examples of how physicians react to the threat of being marginalized, along with their general reluctance to adapt to new technology. Now we get into the “Second Machine Age”101 question as to whether the new digital landscape will reboot the need for doctors and health professionals. Kevin Kelly, a cofounder of Wired, has asserted: “The role tasks of any information-intensive job can be automated. It doesn’t matter if you are a doctor, lawyer, architect, reporter, or even programmer: The robot takeover will be epic.”102 An emergency medicine physician likened the current practice of medicine to a Radio Shack store in his piece “Doctor Dinosaur: Physicians may not be exempt from extinction.”103 In late 2013, Korean doctors threatened to go on an all-out strike if the government went ahead with new telemedicine laws that would support clinical diagnoses to be made remotely.

On either end of it are intelligent human beings who are ready to assume quite different roles from what the history of medicine has established. Patients will always crave and need the human touch from a doctor, but that can be had on a more selective basis with the tools at hand. Instead of doctors being squeezed, resorting to computer automation can actually markedly expand their roles. As Kevin Kelly wrote, “the rote tasks of any information-intensive job can be automated. It doesn’t matter if you are a doctor, lawyer, architect, reporter, or even programmer.”102 The Economist weighed in on this too: “The machines are not just cleverer, but they also have access to far more data. The combination of big data and smart machines will take over some occupations wholesale.”153 But smart doctors need not feel threatened, for their occupation is secure. Letting go and competing on embracing digital medicine may turn out to be the best way to prevent disintermediation and disillusionment in the long run.


pages: 565 words: 151,129

The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism by Jeremy Rifkin

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3D printing, active measures, additive manufacturing, Airbnb, autonomous vehicles, back-to-the-land, big-box store, bioinformatics, bitcoin, business process, Chris Urmson, clean water, cleantech, cloud computing, collaborative consumption, collaborative economy, Community Supported Agriculture, Computer Numeric Control, computer vision, crowdsourcing, demographic transition, distributed generation, en.wikipedia.org, Frederick Winslow Taylor, global supply chain, global village, Hacker Ethic, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invisible hand, Isaac Newton, James Watt: steam engine, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Julian Assange, Kickstarter, knowledge worker, labour mobility, Mahatma Gandhi, manufacturing employment, Mark Zuckerberg, market design, mass immigration, means of production, meta analysis, meta-analysis, natural language processing, new economy, New Urbanism, nuclear winter, Occupy movement, off grid, oil shale / tar sands, pattern recognition, peer-to-peer, peer-to-peer lending, personalized medicine, phenotype, planetary scale, price discrimination, profit motive, QR code, RAND corporation, randomized controlled trial, Ray Kurzweil, RFID, Richard Stallman, risk/return, Ronald Coase, search inside the book, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, smart grid, smart meter, social web, software as a service, spectrum auction, Steve Jobs, Stewart Brand, the built environment, The Nature of the Firm, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, too big to fail, transaction costs, urban planning, Watson beat the top human players on Jeopardy!, web application, Whole Earth Catalog, Whole Earth Review, WikiLeaks, working poor, zero-sum game, Zipcar

In the United States, between 1982 and 2002, steel production rose from 75 million tons to 120 million tons, while the number of steel workers declined from 289,000 to 74,000.13 American and European politicians, and the general public, blame blue collar job losses on the relocation of manufacturing to cheap labor markets like China. The fact is that something more consequential has taken place. Between 1995 and 2002, 22 million manufacturing jobs were eliminated in the global economy while global production increased by more than 30 percent worldwide. The United States lost 11 percent of its manufacturing jobs to automation. Even China shed 16 million factory workers while increasing its productivity with IT and robotics, allowing it to produce more output, more cheaply, with fewer workers.14 Manufacturers that have long relied on cheap labor in their Chinese production facilities are bringing production back home with advanced robotics that are cheaper and more efficient than their Chinese workforces. At Philips’s new electronic factory in the Netherlands, the 128 robot arms work at such a quick pace that they have to be put behind glass cases so that the handful of supervisors aren’t injured.


pages: 396 words: 117,149

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos

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3D printing, Albert Einstein, Amazon Mechanical Turk, Arthur Eddington, basic income, Bayesian statistics, Benoit Mandelbrot, bioinformatics, Black Swan, Brownian motion, cellular automata, Claude Shannon: information theory, combinatorial explosion, computer vision, constrained optimization, correlation does not imply causation, creative destruction, crowdsourcing, Danny Hillis, data is the new oil, double helix, Douglas Hofstadter, Erik Brynjolfsson, experimental subject, Filter Bubble, future of work, global village, Google Glasses, Gödel, Escher, Bach, information retrieval, job automation, John Markoff, John Snow's cholera map, John von Neumann, Joseph Schumpeter, Kevin Kelly, lone genius, mandelbrot fractal, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, Narrative Science, Nate Silver, natural language processing, Netflix Prize, Network effects, NP-complete, off grid, P = NP, PageRank, pattern recognition, phenotype, planetary scale, pre–internet, random walk, Ray Kurzweil, recommendation engine, Richard Feynman, Richard Feynman, Second Machine Age, self-driving car, Silicon Valley, speech recognition, statistical model, Stephen Hawking, Steven Levy, Steven Pinker, superintelligent machines, the scientific method, The Signal and the Noise by Nate Silver, theory of mind, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, white flight, zero-sum game

If computers make us smarter, computers running the Master Algorithm will make us feel like geniuses. Technological progress will noticeably speed up, not just in computer science but in many different fields. This in turn will add to economic growth and speed poverty’s decline. With the Master Algorithm to help synthesize and distribute knowledge, the intelligence of an organization will be more than the sum of its parts, not less. Routine jobs will be automated and replaced by more interesting ones. Every job will be done better than it is today, whether by a better-trained human, a computer, or a combination of the two. Stock-market crashes will be fewer and smaller. With a fine grid of sensors covering the globe and learned models to make sense of its output moment by moment, we will no longer be flying blind; the health of our planet will take a turn for the better.

Speech recognition is hard for computers because it’s hard to fill in the blanks—literally, the sounds speakers routinely elide—when you have no idea what the person is talking about. Algorithms can predict stock fluctuations but have no clue how they relate to politics. The more context a job requires, the less likely a computer will be able to do it soon. Common sense is important not just because your mom taught you so, but because computers don’t have it. The best way to not lose your job is to automate it yourself. Then you’ll have time for all the parts of it that you didn’t before and that a computer won’t be able to do any time soon. (If there aren’t any, stay ahead of the curve and get a new job now.) If a computer has learned to do your job, don’t try to compete with it; harness it. H&R Block is still in business, but tax preparers’ jobs are much less dreary than they used to be, now that computers do most of the grunge work.


pages: 431 words: 129,071

Selfie: How We Became So Self-Obsessed and What It's Doing to Us by Will Storr

Albert Einstein, autonomous vehicles, banking crisis, bitcoin, book scanning, computer age, correlation does not imply causation, Donald Trump, Douglas Engelbart, Douglas Engelbart, Elon Musk, en.wikipedia.org, gig economy, greed is good, invisible hand, job automation, John Markoff, Lyft, Menlo Park, meta analysis, meta-analysis, Mont Pelerin Society, mortgage debt, Mother of all demos, Nixon shock, Peter Thiel, QWERTY keyboard, rising living standards, road to serfdom, Robert Gordon, Ronald Reagan, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, Silicon Valley startup, Steve Jobs, Steven Levy, Stewart Brand, The Future of Employment, Tim Cook: Apple, Uber and Lyft, War on Poverty, Whole Earth Catalog

It was then that, feeling ignored and resentful (and, in many cases, racist), a number of working-class Democrats deserted the party for the Republicans. In 1964, 55 per cent of all working-class voters were Democrats. By 1980, that number had fallen to 35 per cent. Under the inequalities of neoliberalism, the white working class suffered. The new era of globalization it brought about saw some of the manufacturing and service industries they relied upon moving overseas. Many others lost their jobs because of automation, the effects of which a more collectively minded state might have sought to mitigate. Whilst plenty of people have become better off, since the 1970s, a good deal of others have seen the worth of their paychecks stall or fall. The average real income for the bottom 90 per cent of earners in the US, for example, has pretty much stagnated. It was $35,411 in 1972, it peaked at $37,053 in 2000 and, by 2013, had fallen to $31,652.

It did, facilitating and accelerating the neoliberal project of globalization immensely from the 1990s onwards. It has plenty in store for the future, too, with automation and artificial intelligence predicted to further decimate middle- and working-class jobs. There are 1.7 million truck drivers in the US alone whose livelihoods are at risk from the introduction of autonomous vehicles. Researchers at the University of Oxford have predicted that, by 2033, nearly half of all US jobs could be automated. The technologists promised us a ‘Long Boom’. They didn’t tell us that boom would be directed mostly at the top. It was another Silicon Valley product, social media, that enabled Donald Trump to connect directly with his supporters, bypassing traditional journalists and undermining their reporting by calling them liars. It’s true that some of his strongest support came from white males without a college degree, who are among those least likely to actually use the internet.


pages: 296 words: 87,299

Portfolios of the poor: how the world's poor live on $2 a day by Daryl Collins, Jonathan Morduch, Stuart Rutherford

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Cass Sunstein, clean water, failed state, financial innovation, financial intermediation, income per capita, informal economy, job automation, M-Pesa, mental accounting, microcredit, moral hazard, profit motive, purchasing power parity, RAND corporation, randomized controlled trial, The Fortune at the Bottom of the Pyramid, transaction costs

Many South African diary households belonged to clubs of this sort, and their most common answer to this question was that club membership was the surest way to discipline themselves to save for a particular event. “You feel compelled to contribute your payment. If you don’t do that, [it] is like you are letting your friends down. So it is better because you make your payment no matter what.” Savings clubs, then, do the job that automated payments into savings accounts, or “stop orders” do for earners in rich economies: they shift money into a “hands off ” account, acting as a guard against the temptation to spend spare money in trivial ways. In this, they play important psychological and social roles, building on commonsense notions that have only been recently recognized by behavioral economists.11 The basic idea is that many people, both rich and poor, are often caught in a bind.


pages: 176 words: 55,819

pages: 124 words: 39,011

Beyond Outrage: Expanded Edition: What Has Gone Wrong With Our Economy and Our Democracy, and How to Fix It by Robert B. Reich

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, affirmative action, banking crisis, carried interest, collateralized debt obligation, collective bargaining, Credit Default Swap, credit default swaps / collateralized debt obligations, desegregation, full employment, Home mortgage interest deduction, job automation, Mahatma Gandhi, minimum wage unemployment, money market fund, new economy, Occupy movement, offshore financial centre, Plutocrats, plutocrats, Ponzi scheme, race to the bottom, Ronald Reagan, single-payer health, special drawing rights, The Wealth of Nations by Adam Smith, Tim Cook: Apple, too big to fail, trickle-down economics, women in the workforce, working poor, zero-sum game

It’s no mere coincidence that over the last century the top earners’ share of the nation’s total income peaked twice, in 1928 and 2007—the two years just preceding the biggest downturns. In the late 1970s, the middle class began to weaken. The two lines began to diverge: Output per hour—a measure of productivity—continued to rise. But real hourly compensation was left in the dust. This was mainly because new technologies—container ships, satellite communications, eventually computers and the Internet—started to undermine any American job that could be automated or done more cheaply abroad. Factories remaining in the United States have shed workers as they automated. So has the service sector. But contrary to popular mythology, trade and technology have not reduced the overall number of American jobs; their more profound effect has been on pay. As I noted, jobs slowly returned from the depths of the Great Recession, but in order to get them, many workers had to accept lower pay than before.


pages: 477 words: 135,607

The Box: How the Shipping Container Made the World Smaller and the World Economy Bigger by Marc Levinson

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air freight, anti-communist, barriers to entry, Bay Area Rapid Transit, British Empire, call centre, collective bargaining, conceptual framework, David Ricardo: comparative advantage, deindustrialization, deskilling, Edward Glaeser, Erik Brynjolfsson, full employment, global supply chain, intermodal, Isaac Newton, job automation, knowledge economy, Malcom McLean invented shipping containers, manufacturing employment, Network effects, New Economic Geography, new economy, oil shock, Panamax, Port of Oakland, post-Panamax, Productivity paradox, refrigerator car, South China Sea, trade route, Works Progress Administration, Yom Kippur War, zero-sum game

Gleason alleged that other ship lines were trying to evade royalty payments by encouraging shippers to pack their cargo on pallets rather than in containers. “This is a clear-cut threat to our existing collective bargaining agreement and to the royalty program,” he charged in late 1961. Longshore hours worked in December 1961 were down 4 percent from the previous year and down 20 percent from December 1956, but there was still no compensation being paid out to the men whose work had diminished.35 Job security in the face of automation thus became the overwhelming union concern as contract negotiations began in 1962. Job security, though, played differently in different places. New York leader Frank Field demanded that the ILA negotiate for a portwide seniority system: business at his own Local 858’s docks, in lower Manhattan, was drying up, but the customary pier-specific seniority meant that displaced Manhattan longshoremen could not easily find work on other piers.


pages: 331 words: 104,366

Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins by Garry Kasparov

3D printing, Ada Lovelace, AI winter, Albert Einstein, AltaVista, barriers to entry, Berlin Wall, business process, call centre, clean water, computer age, Daniel Kahneman / Amos Tversky, David Brooks, Donald Trump, Douglas Hofstadter, Drosophila, Elon Musk, Erik Brynjolfsson, factory automation, Freestyle chess, Gödel, Escher, Bach, job automation, Leonard Kleinrock, Mikhail Gorbachev, Nate Silver, Norbert Wiener, packet switching, pattern recognition, Ray Kurzweil, Richard Feynman, Richard Feynman, rising living standards, rolodex, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, Skype, speech recognition, stem cell, Stephen Hawking, Steven Pinker, technological singularity, The Coming Technological Singularity, The Signal and the Noise by Nate Silver, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, zero-sum game

With every new encroachment of machines, the voices of panic and doubt are heard, and they are only getting louder today. This is partly due to the differences in what, and who, is being replaced. The horses and oxen couldn’t write letters to the editor when cars and tractors came along. Unskilled laborers also lacked much of a voice, and were often considered lucky to be freed from their backbreaking toil. So it went over the decades of the twentieth century, with countless jobs lost or transformed by automation. Entire professions disappeared with little time to mourn them. The elevator operators’ union was seventeen thousand strong in 1920, although its ability to paralyze cities with strikes like the one its members staged in New York in September 1945 surely cost them more than a few mourners when automatic push-button elevators began to replace them in the 1950s. According to the Associated Press, “Thousands struggled up stairways that seemed endless, including the Empire State Building, tallest structure in the world.”

You can’t discard the downsides of globalization while keeping the benefits. It’s a privilege to be able to focus on the negative potential of world-changing breakthroughs like artificial intelligence. As real as these issues may be, we will not solve them unless we keep innovating even more ambitiously, creating solutions and new problems, and yet more solutions, as we always have. The United States needs to replace the jobs being lost to automation, but it needs new jobs to build the future instead of trying to bring back jobs from the past. It can be done and it has been done before. Here I’m not referring to the 30 percent of Americans who lived on farms in 1920, down below 2 percent nearly a century later, but to a much more recent retooling. The launch of the tiny Sputnik device by Sergey Korolyov on October 7, 1957, turned the space race into a sprint that lasted for decades.


pages: 602 words: 177,874

Thank You for Being Late: An Optimist's Guide to Thriving in the Age of Accelerations by Thomas L. Friedman

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3D printing, additive manufacturing, affirmative action, Airbnb, AltaVista, Amazon Web Services, autonomous vehicles, Ayatollah Khomeini, barriers to entry, Berlin Wall, Bernie Sanders, bitcoin, blockchain, Bob Noyce, business process, call centre, centre right, Chris Wanstrath, Clayton Christensen, clean water, cloud computing, corporate social responsibility, creative destruction, crowdsourcing, David Brooks, demand response, demographic dividend, demographic transition, Deng Xiaoping, Donald Trump, Erik Brynjolfsson, failed state, Fall of the Berlin Wall, Ferguson, Missouri, first square of the chessboard / second half of the chessboard, Flash crash, game design, gig economy, global supply chain, illegal immigration, immigration reform, income inequality, indoor plumbing, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the steam engine, inventory management, Irwin Jacobs: Qualcomm, Jeff Bezos, job automation, John Markoff, John von Neumann, Khan Academy, Kickstarter, knowledge economy, knowledge worker, land tenure, linear programming, Live Aid, low skilled workers, Lyft, Marc Andreessen, Mark Zuckerberg, mass immigration, Maui Hawaii, Menlo Park, Mikhail Gorbachev, mutually assured destruction, pattern recognition, planetary scale, pull request, Ralph Waldo Emerson, ransomware, Ray Kurzweil, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Reagan, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, South China Sea, Steve Jobs, supercomputer in your pocket, TaskRabbit, Thomas L Friedman, transaction costs, Transnistria, urban decay, urban planning, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y2K, Yogi Berra, zero-sum game

There is probably no one in America, or anywhere for that matter, who makes their living today producing buggy whips—not since the horse and buggy gave way to the automobile. But it is critical to remember that even 98 percent automation of a job is not the same as 100 percent automation. Why? In the nineteenth century, 98 percent of the labor involved in weaving a yard of cloth got automated. The task went from 100 percent manual labor to 2 percent. “And what happened?” asked Bessen. “The number of weaver jobs increased.” Why? “Because when you automate a job that has largely been done manually, you make it hugely more productive.” And when that happens, he explained, “prices go down and demand goes up” for the product. At the beginning of the nineteenth century, many people had one set of clothes—and they were all man-made. And by the end of that century, most people had multiple sets of clothing, drapes on their windows, rugs on their floors, and upholstery on their furniture.


pages: 238 words: 73,824

Makers by Chris Anderson

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3D printing, Airbnb, Any sufficiently advanced technology is indistinguishable from magic, Apple II, autonomous vehicles, barriers to entry, Buckminster Fuller, Build a better mousetrap, business process, commoditize, Computer Numeric Control, crowdsourcing, dark matter, David Ricardo: comparative advantage, death of newspapers, dematerialisation, Elon Musk, factory automation, Firefox, future of work, global supply chain, global village, industrial robot, interchangeable parts, Internet of things, inventory management, James Hargreaves, James Watt: steam engine, Jeff Bezos, job automation, Joseph Schumpeter, Kickstarter, Lean Startup, manufacturing employment, Mark Zuckerberg, means of production, Menlo Park, Network effects, profit maximization, QR code, race to the bottom, Richard Feynman, Richard Feynman, Ronald Coase, Rubik’s Cube, self-driving car, side project, Silicon Valley, Silicon Valley startup, Skype, slashdot, South of Market, San Francisco, spinning jenny, Startup school, stem cell, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, supply-chain management, The Nature of the Firm, The Wealth of Nations by Adam Smith, transaction costs, trickle-down economics, Whole Earth Catalog, X Prize, Y Combinator

To be sure, the Tesla factory is a special case. It got what amounts to a huge subsidy in its portion of the old NUMMI plant, which it was able to buy for just $43 million, complete with lots of functioning equipment. As a relatively new car company (it was founded in 2003), it didn’t have to inherit the pension obligations and labor unions of the Detroit giants, nor did it face pressure to preserve jobs rather than automate. There’s the small matter of the half-billion-dollar federal loan it got in 2010. And let’s face it: it could still fail. It’s trying to break into the car industry with an expensive vehicle using bleeding-edge pure electric technology in a world where even the giants are having trouble getting people to pay extra for decade-old hybrid technology. But whatever happens to Tesla, its production model will triumph.


pages: 272 words: 64,626

Eat People: And Other Unapologetic Rules for Game-Changing Entrepreneurs by Andy Kessler

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23andMe, Andy Kessler, bank run, barriers to entry, Berlin Wall, Bob Noyce, British Empire, business process, California gold rush, carbon footprint, Cass Sunstein, cloud computing, collateralized debt obligation, collective bargaining, commoditize, computer age, creative destruction, disintermediation, Douglas Engelbart, Eugene Fama: efficient market hypothesis, fiat currency, Firefox, Fractional reserve banking, George Gilder, Gordon Gekko, greed is good, income inequality, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, Joseph Schumpeter, knowledge economy, knowledge worker, libertarian paternalism, low skilled workers, Mark Zuckerberg, McMansion, Netflix Prize, packet switching, personalized medicine, pets.com, prediction markets, pre–internet, profit motive, race to the bottom, Richard Thaler, risk tolerance, risk-adjusted returns, Silicon Valley, six sigma, Skype, social graph, Steve Jobs, The Wealth of Nations by Adam Smith, transcontinental railway, transfer pricing, wealth creators, Yogi Berra

Transitioning from an agricultural to an industrial economy meant automating farming—tractors, combines, better seeds, praying for rain—and it worked. Down from maybe 80 percent of American colonists working on farms, today just 3 percent of the U.S. population feeds the rest of us—so you and I don’t have to get up at 5:30 in the morning to milk the chickens. That’s progress with a capital P. We got rid of factory jobs, either through automation or by exporting them to China and India. Again, capital P progress, because it’s really hot in those steel mills, from what I’ve been told. I think I saw one in a Tom Cruise movie once. We’re now an economy of service workers at far greater risk of getting paper cuts than losing a limb at the mill. But now we’re in the middle of another transition, from that postindustrial “would you like those fries Supersized” world of the eighties and nineties to a more pure knowledge-based, brainfueled something.


pages: 238 words: 68,914

Where Does It Hurt?: An Entrepreneur's Guide to Fixing Health Care by Jonathan Bush, Stephen Baker

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Affordable Care Act / Obamacare, Atul Gawande, barriers to entry, Clayton Christensen, commoditize, informal economy, inventory management, job automation, knowledge economy, lifelogging, obamacare, personalized medicine, ride hailing / ride sharing, Ronald Reagan, Silicon Valley, Steve Jobs, web application, women in the workforce, working poor

They don’t know how. They haven’t been disrupted. Consider this: In 1990, according to Bob Kocher, there were ten people supporting each doctor in America. Some, like nurses, helped with patient care. Others, such as administrators, receptionists, and technicians, kept the business running. In the quarter century since then, we’ve had a computer revolution. We’ve gone online. Millions of jobs have been automated and outsourced. But in that same quarter century, hospital staffs have become bloated, and now there are sixteen people supporting each doctor. Half of them are administrators. This isn’t just negative productivity, it’s insanity. Just picture the inefficiency. A single patient lies in a hospital bed. A doctor walks in with sixteen other people. That patient’s bill not only must underwrite all of the fabulous technology in the hospital, and its research, but it must also pay the salaries and benefits of that large contingent that can barely squeeze into the room.


pages: 222 words: 70,132

Move Fast and Break Things: How Facebook, Google, and Amazon Cornered Culture and Undermined Democracy by Jonathan Taplin

1960s counterculture, 3D printing, affirmative action, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, American Legislative Exchange Council, Apple's 1984 Super Bowl advert, back-to-the-land, barriers to entry, basic income, battle of ideas, big data - Walmart - Pop Tarts, bitcoin, Brewster Kahle, Buckminster Fuller, Burning Man, Clayton Christensen, commoditize, creative destruction, crony capitalism, crowdsourcing, data is the new oil, David Brooks, David Graeber, don't be evil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Dynabook, Edward Snowden, Elon Musk, equal pay for equal work, Erik Brynjolfsson, future of journalism, future of work, George Akerlof, George Gilder, Google bus, Hacker Ethic, Howard Rheingold, income inequality, informal economy, information asymmetry, information retrieval, Internet Archive, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, Kevin Kelly, Kickstarter, labor-force participation, life extension, Marc Andreessen, Mark Zuckerberg, Menlo Park, Metcalfe’s law, Mother of all demos, move fast and break things, move fast and break things, natural language processing, Network effects, new economy, Norbert Wiener, offshore financial centre, packet switching, Paul Graham, Peter Thiel, Plutocrats, plutocrats, pre–internet, Ray Kurzweil, recommendation engine, rent-seeking, revision control, Robert Bork, Robert Gordon, Robert Metcalfe, Ronald Reagan, Sand Hill Road, secular stagnation, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, smart grid, Snapchat, software is eating the world, Steve Jobs, Stewart Brand, technoutopianism, The Chicago School, The Market for Lemons, Tim Cook: Apple, trade route, transfer pricing, trickle-down economics, Tyler Cowen: Great Stagnation, universal basic income, unpaid internship, We wanted flying cars, instead we got 140 characters, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator

The notion that a fifty-year-old autoworker replaced by a robot is going to retrain himself as a software coder and apply for work at Google seems to be a pipe dream that only someone as rich and insulated as Marc Andreessen could conceive. But that is not to say that we shouldn’t think about Keynes’s and Andreessen’s vision of a world in which most of us have a lot of leisure time. If Frey and Osborne are right, and 47 percent of jobs may be automated in the next two decades, then we face one of two possible futures. The dystopian future of mass unemployment and psychological alienation leading to deep social unrest is one we have already seen in Blade Runner. The only present remedy is to create millions of low-wage “bullshit jobs”—the writer David Graeber’s term. Graeber notes, “Huge swaths of people, in Europe and North America in particular, spend their entire working lives performing tasks they believe to be unnecessary.


pages: 374 words: 114,600

The Quants by Scott Patterson

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Albert Einstein, asset allocation, automated trading system, beat the dealer, Benoit Mandelbrot, Bernie Madoff, Bernie Sanders, Black Swan, Black-Scholes formula, Bonfire of the Vanities, Brownian motion, buttonwood tree, buy low sell high, capital asset pricing model, centralized clearinghouse, Claude Shannon: information theory, cloud computing, collapse of Lehman Brothers, collateralized debt obligation, commoditize, computerized trading, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, Doomsday Clock, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, fixed income, Gordon Gekko, greed is good, Haight Ashbury, I will remember that I didn’t make the world, and it doesn’t satisfy my equations, index fund, invention of the telegraph, invisible hand, Isaac Newton, job automation, John Meriwether, John Nash: game theory, law of one price, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, margin call, merger arbitrage, money market fund, Myron Scholes, NetJets, new economy, offshore financial centre, old-boy network, Paul Lévy, Paul Samuelson, Ponzi scheme, quantitative hedge fund, quantitative trading / quantitative finance, race to the bottom, random walk, Renaissance Technologies, risk-adjusted returns, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, Sergey Aleynikov, short selling, South Sea Bubble, speech recognition, statistical arbitrage, The Chicago School, The Great Moderation, The Predators' Ball, too big to fail, transaction costs, value at risk, volatility smile, yield curve, éminence grise

Tuttle’s physics background gave him the tools to understand many of the complex trades PDT executed. But since he didn’t have any computer programming skills, it limited his ability to design and implement models. Instead, he became PDT’s “human trader.” At the time, there were still certain markets, such as stock index futures, that weren’t fully automatic. Trades spat out by PDT’s models had to be called in over the telephone to other desks at Morgan. That was Tuttle’s job. The automated trading system didn’t always go smoothly. Once PDT mistakenly sold roughly $80 million worth of stock in about fifteen minutes due to a bug in the system. Another time Reed, who was running the Japanese stock system at the time, asked another trader to cover for him. “Just hit Y every time it signals a trade,” he said. He failed to mention the need to also hit enter. None of the trades went through properly.


pages: 390 words: 109,870

Radicals Chasing Utopia: Inside the Rogue Movements Trying to Change the World by Jamie Bartlett

Andrew Keen, back-to-the-land, Bernie Sanders, bitcoin, blockchain, blue-collar work, brain emulation, centre right, clean water, cryptocurrency, Donald Trump, drone strike, Elon Musk, energy security, ethereum blockchain, failed state, gig economy, hydraulic fracturing, income inequality, Intergovernmental Panel on Climate Change (IPCC), Jaron Lanier, job automation, John Markoff, Joseph Schumpeter, life extension, Occupy movement, off grid, Peter Thiel, post-industrial society, postnationalism / post nation state, precariat, QR code, Ray Kurzweil, RFID, Rosa Parks, Satoshi Nakamoto, self-driving car, Silicon Valley, Silicon Valley startup, Skype, smart contracts, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, technoutopianism

That is the paradox of the radical. Their energy, imagination and passion might save us, but these very attributes might also lead to ruin and desperation. Yet for all this, radicals remain our best hope. The trends that led us to these remarkable years show no sign of abating. If anything, they will intensify. What happens if, as researchers from the University of Oxford predict, roughly half of all US jobs are automated and taken over by computers by 2033? When everything in our house, our car and our workplace is connected to the internet, all collected, stored and used by mega-companies based in California? Or if, as predicted by the United Nations, by 2050 the population hits 10 billion, half of them facing extreme water shortages, and 250 million climate-change refugees are on the move looking for habitable places to live?


pages: 574 words: 164,509

Superintelligence: Paths, Dangers, Strategies by Nick Bostrom

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agricultural Revolution, AI winter, Albert Einstein, algorithmic trading, anthropic principle, anti-communist, artificial general intelligence, autonomous vehicles, barriers to entry, Bayesian statistics, bioinformatics, brain emulation, cloud computing, combinatorial explosion, computer vision, cosmological constant, dark matter, DARPA: Urban Challenge, data acquisition, delayed gratification, demographic transition, Donald Knuth, Douglas Hofstadter, Drosophila, Elon Musk, en.wikipedia.org, endogenous growth, epigenetics, fear of failure, Flash crash, Flynn Effect, friendly AI, Gödel, Escher, Bach, income inequality, industrial robot, informal economy, information retrieval, interchangeable parts, iterative process, job automation, John Markoff, John von Neumann, knowledge worker, Menlo Park, meta analysis, meta-analysis, mutually assured destruction, Nash equilibrium, Netflix Prize, new economy, Norbert Wiener, NP-complete, nuclear winter, optical character recognition, pattern recognition, performance metric, phenotype, prediction markets, price stability, principal–agent problem, race to the bottom, random walk, Ray Kurzweil, recommendation engine, reversible computing, social graph, speech recognition, Stanislav Petrov, statistical model, stem cell, Stephen Hawking, strong AI, superintelligent machines, supervolcano, technological singularity, technoutopianism, The Coming Technological Singularity, The Nature of the Firm, Thomas Kuhn: the structure of scientific revolutions, transaction costs, Turing machine, Vernor Vinge, Watson beat the top human players on Jeopardy!, World Values Survey, zero-sum game

Such preferences could also have ideological or religious roots. Just as many Muslims and Jews shun food prepared in ways they classify as haram or treif, so there might be groups in the future that eschew products whose manufacture involved unsanctioned use of machine intelligence. What hinges on this? To the extent that cheap machine labor can substitute for human labor, human jobs may disappear. Fears about automation and job loss are of course not new. Concerns about technological unemployment have surfaced periodically, at least since the Industrial Revolution; and quite a few professions have in fact gone the way of the English weavers and textile artisans who in the early nineteenth century united under the banner of the folkloric “General Ludd” to fight against the introduction of mechanized looms.


pages: 510 words: 120,048

Who Owns the Future? by Jaron Lanier

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3D printing, 4chan, Affordable Care Act / Obamacare, Airbnb, augmented reality, automated trading system, barriers to entry, bitcoin, book scanning, Burning Man, call centre, carbon footprint, cloud computing, commoditize, computer age, crowdsourcing, David Brooks, David Graeber, delayed gratification, digital Maoism, Douglas Engelbart, en.wikipedia.org, Everything should be made as simple as possible, facts on the ground, Filter Bubble, financial deregulation, Fractional reserve banking, Francis Fukuyama: the end of history, George Akerlof, global supply chain, global village, Haight Ashbury, hive mind, if you build it, they will come, income inequality, informal economy, information asymmetry, invisible hand, Jacquard loom, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Khan Academy, Kickstarter, Kodak vs Instagram, life extension, Long Term Capital Management, Marc Andreessen, Mark Zuckerberg, meta analysis, meta-analysis, Metcalfe’s law, moral hazard, mutually assured destruction, Network effects, new economy, Norbert Wiener, obamacare, packet switching, Peter Thiel, place-making, Plutocrats, plutocrats, Ponzi scheme, post-oil, pre–internet, race to the bottom, Ray Kurzweil, rent-seeking, reversible computing, Richard Feynman, Richard Feynman, Ronald Reagan, self-driving car, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, smart meter, stem cell, Steve Jobs, Steve Wozniak, Stewart Brand, Ted Nelson, The Market for Lemons, Thomas Malthus, too big to fail, trickle-down economics, Turing test, Vannevar Bush, WikiLeaks, zero-sum game

The key question isn’t “How much will be automated?” It’s how we’ll conceive of whatever can’t be automated at a given time. Even if there are new demands for people to perform new tasks in support of what we perceive as automation, we might apply antihuman values that define the new roles as not being “genuine work.” Maybe people will be expected to “share” instead. So the right question is “How many jobs might be lost to automation if we think about automation the wrong way?” One of the strange, tragic aspects of our technological moment is that the most celebrated information gadgets, like our phones and tablets, are made by hand in gigantic factories, mostly in southern China, and largely by people who work insanely hard in worrisome environments. Looking at the latest advances in robotics and automated manufacturing, it’s hard not to wonder when the labors of these hordes of new potential Luddites might become suddenly obsolete.

In that case it would cost real money to use the resources needed to start an occult Wall Street scheme or to dangle “free” Internet bait in the hopes of trapping a population into paying for visibility. The benefit of a general “spy data tax” would be a lessening of “scammy” entrepreneurship and a corresponding increase in the funding of genuinely productive new ventures. Meanwhile, as more and more jobs are lost to automation, social welfare funds would burst with new revenues to cope with the deluge. In the current American climate, what I just said would be called “fighting words.” Most Americans would probably fear that such a policy would promote unlimited growth of government bureaucracy, and that would ultimately lead to a loss of both liberty and innovation. The argument against the idea would generally go as follows: Since everything is becoming more and more software-mediated, a spy data tax would not lead to a bureaucracy of a fixed size, like the ones that deal with the public airwaves.


pages: 308 words: 84,713

The Glass Cage: Automation and Us by Nicholas Carr

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Airbnb, Airbus A320, Andy Kessler, Atul Gawande, autonomous vehicles, Bernard Ziegler, business process, call centre, Captain Sullenberger Hudson, Checklist Manifesto, cloud computing, computerized trading, David Brooks, deliberate practice, deskilling, digital map, Douglas Engelbart, drone strike, Elon Musk, Erik Brynjolfsson, Flash crash, Frank Gehry, Frank Levy and Richard Murnane: The New Division of Labor, Frederick Winslow Taylor, future of work, global supply chain, Google Glasses, Google Hangouts, High speed trading, indoor plumbing, industrial robot, Internet of things, Jacquard loom, Jacquard loom, James Watt: steam engine, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kevin Kelly, knowledge worker, Lyft, Marc Andreessen, Mark Zuckerberg, means of production, natural language processing, new economy, Nicholas Carr, Norbert Wiener, Oculus Rift, pattern recognition, Peter Thiel, place-making, Plutocrats, plutocrats, profit motive, Ralph Waldo Emerson, RAND corporation, randomized controlled trial, Ray Kurzweil, recommendation engine, robot derives from the Czech word robota Czech, meaning slave, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley ideology, software is eating the world, Stephen Hawking, Steve Jobs, TaskRabbit, technoutopianism, The Wealth of Nations by Adam Smith, turn-by-turn navigation, US Airways Flight 1549, Watson beat the top human players on Jeopardy!, William Langewiesche

“The lesson,” he wrote, “should be increasingly clear—it is not necessarily true that highly complex equipment requires skilled operators. The ‘skill’ can be built into the machine.”36 IT MAY seem as though a factory worker operating a noisy industrial machine has little in common with a highly educated professional entering esoteric information through a touchscreen or keyboard in a quiet office. But in both cases, we see a person sharing a job with an automated system—with another party. And, as Bright’s work and subsequent studies of automation make clear, the sophistication of the system, whether it operates mechanically or digitally, determines how roles and responsibilities are divided and, in turn, the set of skills each party is called upon to exercise. As more skills are built into the machine, it assumes more control over the work, and the worker’s opportunity to engage in and develop deeper talents, such as those involved in interpretation and judgment, dwindles.


pages: 332 words: 89,668

Two Nations, Indivisible: A History of Inequality in America: A History of Inequality in America by Jamie Bronstein

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Affordable Care Act / Obamacare, back-to-the-land, barriers to entry, basic income, Bernie Sanders, big-box store, blue-collar work, Branko Milanovic, British Empire, Capital in the Twenty-First Century by Thomas Piketty, clean water, cognitive dissonance, collateralized debt obligation, collective bargaining, Community Supported Agriculture, corporate personhood, crony capitalism, deindustrialization, desegregation, Donald Trump, ending welfare as we know it, Frederick Winslow Taylor, full employment, Gini coefficient, income inequality, interchangeable parts, invisible hand, job automation, John Maynard Keynes: technological unemployment, labor-force participation, land reform, land tenure, low skilled workers, low-wage service sector, mandatory minimum, mass incarceration, minimum wage unemployment, moral hazard, moral panic, mortgage debt, New Urbanism, non-tariff barriers, obamacare, occupational segregation, Occupy movement, oil shock, Plutocrats, plutocrats, price discrimination, race to the bottom, rent control, road to serfdom, Ronald Reagan, Scientific racism, Simon Kuznets, single-payer health, strikebreaker, too big to fail, trade route, transcontinental railway, Triangle Shirtwaist Factory, trickle-down economics, universal basic income, Upton Sinclair, upwardly mobile, urban renewal, wage slave, War on Poverty, women in the workforce, working poor, Works Progress Administration

Over the past few decades, even investment in aspects of our common life once considered crucial for advancement of the economy—research universities, for example, and infrastructure—have been allowed to go begging. Fears about the slowing of the economy in general are met with calls for the education of the workforce, as though that, rather than increasing consumer demand, will guarantee that every individual somehow has a high-paying job. In fact, automation has caused the hollowing out of the wage structure; the highest-paid people continue to be highly paid, while middle- and low-skilled workers conduct a race to the bottom for lower-skilled jobs. Without some degree of redistribution and the provision of more public goods “such as food, housing, education and health care that are necessary for a modern life to go well,” there is no guarantee that economic output will have any relationship to well-being.72 The path of the Patient Protection and Affordable Care Act (ACA, 2010) provides a good illustration of the problems caused by divergent partisan ideologies and powerful framing narratives.


pages: 117 words: 30,654

pages: 843 words: 223,858

The Rise of the Network Society by Manuel Castells

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Apple II, Asian financial crisis, barriers to entry, Big bang: deregulation of the City of London, Bob Noyce, borderless world, British Empire, capital controls, complexity theory, computer age, computerized trading, creative destruction, Credit Default Swap, declining real wages, deindustrialization, delayed gratification, dematerialisation, deskilling, disintermediation, double helix, Douglas Engelbart, Douglas Engelbart, edge city, experimental subject, financial deregulation, financial independence, floating exchange rates, future of work, global village, Gunnar Myrdal, Hacker Ethic, hiring and firing, Howard Rheingold, illegal immigration, income inequality, Induced demand, industrial robot, informal economy, information retrieval, intermodal, invention of the steam engine, invention of the telephone, inventory management, James Watt: steam engine, job automation, job-hopping, John Markoff, knowledge economy, knowledge worker, labor-force participation, labour market flexibility, labour mobility, laissez-faire capitalism, Leonard Kleinrock, low skilled workers, manufacturing employment, Marc Andreessen, Marshall McLuhan, means of production, megacity, Menlo Park, moral panic, new economy, New Urbanism, offshore financial centre, oil shock, open economy, packet switching, Pearl River Delta, peer-to-peer, planetary scale, popular capitalism, popular electronics, post-industrial society, postindustrial economy, prediction markets, Productivity paradox, profit maximization, purchasing power parity, RAND corporation, Robert Gordon, Robert Metcalfe, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, social software, South China Sea, South of Market, San Francisco, special economic zone, spinning jenny, statistical model, Steve Jobs, Steve Wozniak, Ted Nelson, the built environment, the medium is the message, the new new thing, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, total factor productivity, trade liberalization, transaction costs, urban renewal, urban sprawl, zero-sum game

Multi-skilling of jobs and individualization of responsibility were often accompanied by ideologically tailored new titles (for example, “assistant manager” instead of “secretary”), thus enhancing the potential for commitment of clerical workers without correspondingly increasing their professional rewards. Thus, new information technology is redefining work processes, and workers, and therefore employment and occupational structure. While a substantial number of jobs are being upgraded in skills, and sometimes in wages and working conditions in the most dynamic sectors, a large number of jobs are being phased out by automation in both manufacturing and services. These are generally jobs that are not skilled enough to escape to automation but are expensive enough to be worth the investment in technology to replace them. Increasing educational qualifications, either general or specialized, required in the reskilled positions of the occupational structure further segregate the labor force on the basis of education, itself a highly segregated system because it roughly corresponds institutionally to a segregated residential structure.

Yet the prophets of mass unemployment, led by the honorable Club of Rome, argue that such calculations are based on a different historical experience that underestimates the radically new impacts of technologies, whose effects are universal and pervasive because they relate to information processing. Thus, so the argument goes, if manufacturing jobs go the way farmers did, there will not be enough service jobs to replace them because service jobs themselves are being rapidly automated and phased out. They predicted that because this trend was accelerating in the 1990s, mass unemployment would follow.77 The obvious consequence of this analysis is that our societies would have to choose between massive unemployment, with its corollary, the sharp division of society between the employed and the unemployed/occasional workers, or else a redefinition of work and employment, opening the way to a full restructuring of social organization and cultural values.


pages: 238 words: 77,730

pages: 268 words: 75,850

The Formula: How Algorithms Solve All Our Problems-And Create More by Luke Dormehl

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3D printing, algorithmic trading, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, big data - Walmart - Pop Tarts, call centre, Cass Sunstein, Clayton Christensen, commoditize, computer age, death of newspapers, deferred acceptance, Edward Lorenz: Chaos theory, Erik Brynjolfsson, Filter Bubble, Flash crash, Florence Nightingale: pie chart, Frank Levy and Richard Murnane: The New Division of Labor, Google Earth, Google Glasses, High speed trading, Internet Archive, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Kodak vs Instagram, lifelogging, Marshall McLuhan, means of production, Nate Silver, natural language processing, Netflix Prize, pattern recognition, price discrimination, recommendation engine, Richard Thaler, Rosa Parks, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, Slavoj Žižek, social graph, speech recognition, Steve Jobs, Steven Levy, Steven Pinker, Stewart Brand, the scientific method, The Signal and the Noise by Nate Silver, upwardly mobile, Wall-E, Watson beat the top human players on Jeopardy!, Y Combinator

The gorgeous messiness of flesh and blood will prevail!7 This is a sentiment that is still widely argued—particularly when algorithms take on the kind of humanities-oriented fields I have approached in this book. However, it is also necessary to note that drawing a definite line only capable of being crossed by the “gorgeous messiness of [the] flesh” is a little like Levy and Murnane’s statements about which jobs are safe from automation. Certainly, there are plenty of jobs and other areas of life now carried out by algorithm, which were previously thought to have been the sole domain of humans. Facial recognition, for instance, was once considered to be a trait performable only by a select few higher-performing animals—humans among them. Today algorithms employed by Facebook and Google regularly recognize individual faces out of the billions of personal images uploaded by users.


pages: 219 words: 61,720

American Made: Why Making Things Will Return Us to Greatness by Dan Dimicco

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, Affordable Care Act / Obamacare, American energy revolution, American Society of Civil Engineers: Report Card, Bakken shale, barriers to entry, Bernie Madoff, carbon footprint, clean water, crony capitalism, currency manipulation / currency intervention, David Ricardo: comparative advantage, decarbonisation, fear of failure, full employment, Google Glasses, hydraulic fracturing, invisible hand, job automation, knowledge economy, laissez-faire capitalism, Loma Prieta earthquake, manufacturing employment, oil shale / tar sands, Ponzi scheme, profit motive, Report Card for America’s Infrastructure, Ronald Reagan, Silicon Valley, smart grid, smart meter, sovereign wealth fund, The Wealth of Nations by Adam Smith, too big to fail, uranium enrichment, Washington Consensus, Works Progress Administration

I don’t care what your labor costs are—they could be zero—there is no way you can make up for that $32 differential without cheating. It’s flat-out impossible. China’s steel industry is obviously subsidized. They’re producing nearly 820 million tons of steel per year, and they’re losing money. That’s how out of control it is. Yet China continues to overbuild because Beijing wants to maintain the jobs that go into constructing the steel plants, and eventually maintain the smaller number of jobs running these highly automated facilities. Yet we can’t sell steel to China. The barriers to entry are too high. Market forces aren’t allowed to work. We can’t build a steel mill in China, although China can certainly build steel mills here. If you don’t believe me, ask Lakshmi Mittal, the chairman, CEO, and principal owner of ArcelorMittal, the world’s biggest steel company. He wanted to buy a controlling stake in Hunan Valin Steel, one of the major Chinese steel manufacturers.


pages: 268 words: 74,724

Who Needs the Fed?: What Taylor Swift, Uber, and Robots Tell Us About Money, Credit, and Why We Should Abolish America's Central Bank by John Tamny

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Airbnb, bank run, banks create money, Bernie Madoff, bitcoin, Bretton Woods, Carmen Reinhart, corporate raider, correlation does not imply causation, creative destruction, Credit Default Swap, crony capitalism, crowdsourcing, Donald Trump, Downton Abbey, fiat currency, financial innovation, Fractional reserve banking, full employment, George Gilder, Home mortgage interest deduction, Jeff Bezos, job automation, Joseph Schumpeter, Kenneth Rogoff, Kickstarter, liquidity trap, Mark Zuckerberg, market bubble, money market fund, moral hazard, mortgage tax deduction, NetJets, offshore financial centre, oil shock, peak oil, Peter Thiel, price stability, profit motive, quantitative easing, race to the bottom, Ronald Reagan, self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Steve Jobs, The Wealth of Nations by Adam Smith, too big to fail, Uber for X, War on Poverty, yield curve

They should embrace the rise of robots precisely because they love job creation. Robots are credit creation personified. When entrepreneurs borrow dollars with an eye on starting companies, they are borrowing real economic resources. Robots, by their very name, promise cheap resources necessary for entrepreneurialism in abundance. After that, robots will ultimately be the biggest job creators, because aggressive automation will free up humans to do new work by virtue of robots erasing toil that was once essential. Lest we forget, there was a time in American history when just about everyone worked, whether they wanted to or not, on farms, just to survive. Thank goodness technology destroyed lots of agricultural work and freed up Americans to pursue a wide range of vocations off the farm. With their evolution as labor inputs, robots bring the promise of new forms of work that will have us marveling at labor we wasted in the past, and that will make past so-called job destroyers, like wind power, water power, the cotton gin, the car, and the computer, seem small by comparison.


pages: 677 words: 206,548

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It by Marc Goodman

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23andMe, 3D printing, active measures, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, Chelsea Manning, cloud computing, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, Dean Kamen, disintermediation, don't be evil, double helix, Downton Abbey, drone strike, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, John Markoff, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, lifelogging, litecoin, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Metcalfe’s law, mobile money, more computing power than Apollo, move fast and break things, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, off grid, offshore financial centre, optical character recognition, Parag Khanna, pattern recognition, peer-to-peer, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, RAND corporation, ransomware, Ray Kurzweil, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, supply-chain management, technological singularity, telepresence, telepresence robot, Tesla Model S, The Future of Employment, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Wall-E, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, Westphalian system, WikiLeaks, Y Combinator, zero day

Biometric tools will have profound implications not just for undercover cops but for witness relocation programs as well. Anybody who has had a prior life that he wishes to conceal for personal or professional reasons may find it impossible moving forward, and it is not just your physical attributes that may betray you—so might your imperceptible behaviors. On Your Best Behavior A lot of jobs today are being automated; what happens when you extend that concept to very important areas of society like law enforcement? What happens if you start controlling the behavior of criminals or people in general with software-running machines? Those questions, they look like they’re sci-fi but they’re not. JOSÉ PADILHA, BRAZILIAN FILM DIRECTOR When most people think of biometrics, they commonly focus on the measurement of anatomical traits such as our fingers, faces, hands, or eyes.

They can find their ways to any guest’s room and deliver that toothbrush you forgot or the room service you ordered, freeing up staff to work on other tasks. Momentum Machines’ burger bot can crank out 360 perfectly cooked-to-order hamburgers per hour, each with the precise toppings (lettuce, ketchup, onions) requested by the customer. A 2013 study by Oxford University on the future of work conducted a detailed analysis of over seven hundred occupations and concluded that 47 percent of U.S. employees are at high risk of losing their jobs to robotic automation as soon as 2023. Those working in the transportation field (taxi drivers, bus drivers, long-haul truck drivers, FedEx drivers, pizza delivery drivers) face particular risk, with up to a 90 percent certainty that their jobs will be replaced by autonomous vehicles. But it’s not just low-level positions that are at risk. News outlets such as the Associated Press and the Los Angeles Times are using bots and algorithms to automatically write thousands of articles on topics as diverse as homicides, earthquakes, and the latest business earnings.


pages: 757 words: 193,541

The Practice of Cloud System Administration: DevOps and SRE Practices for Web Services, Volume 2 by Thomas A. Limoncelli, Strata R. Chalup, Christina J. Hogan

active measures, Amazon Web Services, anti-pattern, barriers to entry, business process, cloud computing, commoditize, continuous integration, correlation coefficient, database schema, Debian, defense in depth, delayed gratification, DevOps, domain-specific language, en.wikipedia.org, fault tolerance, finite state, Firefox, Google Glasses, information asymmetry, Infrastructure as a Service, intermodal, Internet of things, job automation, job satisfaction, load shedding, loose coupling, Malcom McLean invented shipping containers, Marc Andreessen, place-making, platform as a service, premature optimization, recommendation engine, revision control, risk tolerance, side project, Silicon Valley, software as a service, sorting algorithm, statistical model, Steven Levy, supply-chain management, Toyota Production System, web application, Yogi Berra

Originally the process of painting the metal panels that make up the outer body of the car was a task done by people. It was a slow, delicate, and difficult process requiring great skill. Then a high-power paint sprayer was invented to improve this process. The same person could do a better job, with less wasted paint, in less time. This technology also reduced the amount of skill required, thereby lowering the barrier to entry for this job. However, there was still a car panel painter job. The process had not been automated, but there was a better tool for the job. In the 1970s, auto manufacturing plants automated the car painting process. They deployed robotic painting systems and the job of car panel painter was eliminated. Employees now maintain the robotic painting system, or automation, which is a very different job from painting metal panels. 12.2.2 Example: Machine Configuration In IT we are making a similar transformation.

Puppet manifests (programs) run as root and can change any file on the machine being run on. Therefore it is important that (for example) the Ubuntu team cannot make changes to the Mac team’s files, and vice versa. Doing so would, essentially, give the Ubuntu team access to all the Macs. This is implemented through a simple but powerful permission system. * * * 12.9 Summary The majority of a system administrator’s job should focus on automating SA tasks. A cloud computing system administrator’s goal should be to spend less than half the time doing manual operational work. Tool building optimizes the work done by a system administrator and is an important step on the way to automation. Automation means replacing a human task with one done by software, often working in partnership with a person. Automation starts by having a documented, well-defined, repeatable process.


pages: 566 words: 163,322

The Rise and Fall of Nations: Forces of Change in the Post-Crisis World by Ruchir Sharma

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3D printing, Asian financial crisis, backtesting, bank run, banking crisis, Berlin Wall, Bernie Sanders, BRICs, business climate, business process, call centre, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, central bank independence, centre right, colonial rule, Commodity Super-Cycle, corporate governance, creative destruction, crony capitalism, currency peg, dark matter, debt deflation, deglobalization, deindustrialization, demographic dividend, demographic transition, Deng Xiaoping, Doha Development Round, Donald Trump, Edward Glaeser, Elon Musk, eurozone crisis, failed state, Fall of the Berlin Wall, falling living standards, Francis Fukuyama: the end of history, Freestyle chess, Gini coefficient, hiring and firing, income inequality, indoor plumbing, industrial robot, inflation targeting, Internet of things, Jeff Bezos, job automation, John Markoff, Joseph Schumpeter, Kenneth Rogoff, knowledge economy, labor-force participation, liberal capitalism, Malacca Straits, Mark Zuckerberg, market bubble, mass immigration, megacity, Mexican peso crisis / tequila crisis, mittelstand, moral hazard, New Economic Geography, North Sea oil, oil rush, oil shale / tar sands, oil shock, pattern recognition, Paul Samuelson, Peter Thiel, pets.com, Plutocrats, plutocrats, Ponzi scheme, price stability, Productivity paradox, purchasing power parity, quantitative easing, Ralph Waldo Emerson, random walk, rent-seeking, reserve currency, Ronald Coase, Ronald Reagan, savings glut, secular stagnation, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Simon Kuznets, smart cities, Snapchat, South China Sea, sovereign wealth fund, special economic zone, spectrum auction, Steve Jobs, The Future of Employment, The Wisdom of Crowds, Thomas Malthus, total factor productivity, trade liberalization, trade route, tulip mania, Tyler Cowen: Great Stagnation, unorthodox policies, Washington Consensus, WikiLeaks, women in the workforce, working-age population

This transformation is not about robotic arms providing muscle on the assembly line, they say—it’s about automatons with artificial intelligence capable of “machine learning” and of, one day, designing the assembly line, all powered by the awesome computing capacity of the cloud and big data. In one of the most widely cited forecasts, the Oxford University researchers Carl Benedikt Frey and Michael Osborne predicted in late 2013 that about 47 percent of U.S. jobs are at risk from automation in the next decade or two.12 The most common job for American men is driving, and one forecast has driverless smart cars and trucks replacing them all by 2020. This line of logic parallels many arguments we have heard before. Berkeley’s Machine Intelligence Research Institute has tallied up forecasts for when artificial intelligence (AI) will arrive, and the standard prediction today is that it will be upon us in twenty years.


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Year's Best SF 15 by David G. Hartwell; Kathryn Cramer

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air freight, Black Swan, experimental subject, Georg Cantor, gravity well, job automation, Kuiper Belt, phenotype, semantic web

Salla had fallen from the airship mast and drowned in the waters of Lake Michigan, others had broken their skulls when masonry had fallen on them from improperly lashed cranes, or been crushed under piles of girders that slipped from the pincers of poorly programmed automata. And it wasn’t just the dead men buried in paupers’ graves south of the park that had been affected. Even now, in the city itself, striking workers agitated for better working conditions, or for assurances that they would not lose their jobs to automation. The motto of the Columbian Exhibition was “Not Matter, But Mind; Not Things, But Men,” but Chabane could not help but wonder whether such noble sentiments were any salve to men who had been replaced at their posts by “things” in recent months and years. He knew it came as no comfort to those men who had died in automata-related accidents. But accidents were one thing. A murder was a different matter entirely.


pages: 741 words: 179,454

Extreme Money: Masters of the Universe and the Cult of Risk by Satyajit Das

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affirmative action, Albert Einstein, algorithmic trading, Andy Kessler, Asian financial crisis, asset allocation, asset-backed security, bank run, banking crisis, banks create money, Basel III, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Black Swan, Bonfire of the Vanities, bonus culture, Bretton Woods, BRICs, British Empire, capital asset pricing model, Carmen Reinhart, carried interest, Celtic Tiger, clean water, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, corporate raider, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, debt deflation, Deng Xiaoping, deskilling, discrete time, diversification, diversified portfolio, Doomsday Clock, Edward Thorp, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, eurozone crisis, Fall of the Berlin Wall, financial independence, financial innovation, financial thriller, fixed income, full employment, global reserve currency, Goldman Sachs: Vampire Squid, Gordon Gekko, greed is good, happiness index / gross national happiness, haute cuisine, high net worth, Hyman Minsky, index fund, information asymmetry, interest rate swap, invention of the wheel, invisible hand, Isaac Newton, job automation, Johann Wolfgang von Goethe, John Meriwether, joint-stock company, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, Kevin Kelly, labour market flexibility, laissez-faire capitalism, load shedding, locking in a profit, Long Term Capital Management, Louis Bachelier, margin call, market bubble, market fundamentalism, Marshall McLuhan, Martin Wolf, mega-rich, merger arbitrage, Mikhail Gorbachev, Milgram experiment, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, mutually assured destruction, Myron Scholes, Naomi Klein, negative equity, Network effects, new economy, Nick Leeson, Nixon shock, Northern Rock, nuclear winter, oil shock, Own Your Own Home, Paul Samuelson, pets.com, Philip Mirowski, Plutocrats, plutocrats, Ponzi scheme, price anchoring, price stability, profit maximization, quantitative easing, quantitative trading / quantitative finance, Ralph Nader, RAND corporation, random walk, Ray Kurzweil, regulatory arbitrage, rent control, rent-seeking, reserve currency, Richard Feynman, Richard Feynman, Richard Thaler, Right to Buy, risk-adjusted returns, risk/return, road to serfdom, Robert Shiller, Robert Shiller, Rod Stewart played at Stephen Schwarzman birthday party, rolodex, Ronald Reagan, Ronald Reagan: Tear down this wall, Satyajit Das, savings glut, shareholder value, Sharpe ratio, short selling, Silicon Valley, six sigma, Slavoj Žižek, South Sea Bubble, special economic zone, statistical model, Stephen Hawking, Steve Jobs, survivorship bias, The Chicago School, The Great Moderation, the market place, the medium is the message, The Myth of the Rational Market, The Nature of the Firm, the new new thing, The Predators' Ball, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, trickle-down economics, Turing test, Upton Sinclair, value at risk, Yogi Berra, zero-coupon bond, zero-sum game

Even these investors chased higher returns, encouraging lower-quality loans to be made and repackaged. Investors relied on the rating agencies, who relied on banks, brokers, and various third parties to ensure the quality of the loans. Banks and lenders relied on the rating agencies. The brokers relied on the banks that were buying their loans and the investors buying the securities. Everyone relied on someone else to do their job. The automated models for approving mortgages and rating models for evaluating the quality of ABSs relied on historical data that ignored changes in the mortgage market, especially the deteriorating quality of the loans. They failed to grasp L.P. Hartley’s observation in his novel The Go-Between: “The past is another country; they do things differently there.” In a failure of common sense, smart people spent a lot of time using models and historical data to convince themselves and each other that the risks were low.


pages: 386 words: 122,595

Naked Economics: Undressing the Dismal Science (Fully Revised and Updated) by Charles Wheelan

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affirmative action, Albert Einstein, Andrei Shleifer, barriers to entry, Berlin Wall, Bernie Madoff, Bretton Woods, capital controls, Cass Sunstein, central bank independence, clean water, collapse of Lehman Brothers, congestion charging, creative destruction, Credit Default Swap, crony capitalism, currency manipulation / currency intervention, Daniel Kahneman / Amos Tversky, David Brooks, demographic transition, diversified portfolio, Doha Development Round, Exxon Valdez, financial innovation, fixed income, floating exchange rates, George Akerlof, Gini coefficient, Gordon Gekko, greed is good, happiness index / gross national happiness, Hernando de Soto, income inequality, index fund, interest rate swap, invisible hand, job automation, John Markoff, Joseph Schumpeter, Kenneth Rogoff, libertarian paternalism, low skilled workers, lump of labour, Malacca Straits, market bubble, microcredit, money market fund, money: store of value / unit of account / medium of exchange, Network effects, new economy, open economy, presumed consent, price discrimination, price stability, principal–agent problem, profit maximization, profit motive, purchasing power parity, race to the bottom, RAND corporation, random walk, rent control, Richard Thaler, rising living standards, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Coase, Ronald Reagan, school vouchers, Silicon Valley, Silicon Valley startup, South China Sea, Steve Jobs, The Market for Lemons, the rule of 72, The Wealth of Nations by Adam Smith, Thomas L Friedman, Thomas Malthus, transaction costs, transcontinental railway, trickle-down economics, urban sprawl, Washington Consensus, Yogi Berra, young professional, zero-sum game


pages: 481 words: 125,946

What to Think About Machines That Think: Today's Leading Thinkers on the Age of Machine Intelligence by John Brockman

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3D printing, agricultural Revolution, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, artificial general intelligence, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, clean water, cognitive dissonance, Colonization of Mars, complexity theory, computer age, computer vision, constrained optimization, corporate personhood, cosmological principle, cryptocurrency, cuban missile crisis, Danny Hillis, dark matter, discrete time, Douglas Engelbart, Elon Musk, Emanuel Derman, endowment effect, epigenetics, Ernest Rutherford, experimental economics, Flash crash, friendly AI, functional fixedness, Google Glasses, hive mind, income inequality, information trail, Internet of things, invention of writing, iterative process, Jaron Lanier, job automation, John Markoff, John von Neumann, Kevin Kelly, knowledge worker, loose coupling, microbiome, Moneyball by Michael Lewis explains big data, natural language processing, Network effects, Norbert Wiener, pattern recognition, Peter Singer: altruism, phenotype, planetary scale, Ray Kurzweil, recommendation engine, Republic of Letters, RFID, Richard Thaler, Rory Sutherland, Satyajit Das, Search for Extraterrestrial Intelligence, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, superintelligent machines, supervolcano, the scientific method, The Wisdom of Crowds, theory of mind, Thorstein Veblen, too big to fail, Turing machine, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Y2K

Is there some construction, some bridge, from the digital and virtual to the analog, organic, and real? These threads meet with the merger of human and computer substrates. Smartphones are rapidly becoming indispensable parts of ourselves. The establishment has always questioned the arrival of new media, but adoption of these extensions of ourselves continues apace. A lot of ink has been spilled over the coming conflict between human and computer, be it economic doom, with jobs lost to automation, or military dystopia teeming with drones. Instead, I see a symbiosis developing. And historically, when a new stage of evolution appeared— like eukaryotic cells, or multicellular organisms, or brains—the old system remained and the new system worked with it, not in place of it. This is cause for optimism. If digital computers are an alternative substrate for thinking and consciousness, and digital technology is growing exponentially, then we face an explosion of thinking and awareness.


pages: 223 words: 10,010

The Cost of Inequality: Why Economic Equality Is Essential for Recovery by Stewart Lansley

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banking crisis, Basel III, Big bang: deregulation of the City of London, Bonfire of the Vanities, borderless world, Branko Milanovic, Bretton Woods, British Empire, business process, call centre, capital controls, collective bargaining, corporate governance, corporate raider, correlation does not imply causation, creative destruction, credit crunch, Credit Default Swap, crony capitalism, David Ricardo: comparative advantage, deindustrialization, Edward Glaeser, falling living standards, financial deregulation, financial innovation, Financial Instability Hypothesis, floating exchange rates, full employment, Goldman Sachs: Vampire Squid, high net worth, hiring and firing, Hyman Minsky, income inequality, James Dyson, Jeff Bezos, job automation, John Meriwether, Joseph Schumpeter, Kenneth Rogoff, knowledge economy, laissez-faire capitalism, light touch regulation, Long Term Capital Management, low skilled workers, manufacturing employment, market bubble, Martin Wolf, mittelstand, mobile money, Mont Pelerin Society, Myron Scholes, new economy, Nick Leeson, North Sea oil, Northern Rock, offshore financial centre, oil shock, Plutocrats, plutocrats, Plutonomy: Buying Luxury, Explaining Global Imbalances, Right to Buy, rising living standards, Robert Shiller, Robert Shiller, Ronald Reagan, savings glut, shareholder value, The Great Moderation, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas Malthus, too big to fail, Tyler Cowen: Great Stagnation, Washington Consensus, Winter of Discontent, working-age population

This shows a growth in the number of jobs at the top tail of the distribution—business executives, senior managers, consultants, data processors, software engineers; a smaller rise in the number of low paid jobs in the lower tail—cleaners, hairdressers, shop assistants and call centre workers; and sharp falls in the number of jobs paying middle wages in 1979—machine setters, foundry labourers, plant and rail signal operatives and a range of routine clerical jobs that have become automated.112 In the immediate post-war decades—across mature economies—there used to be more of a continuum in jobs, wages and opportunities with more intermediate, middleskill, middle-paying work that filled the gap between semi-and unskilled blue-collar and higher paying professional jobs. These provided work for a sizeable group once described by Philip Gould, Labour’s chief pollster under Tony Blair, and one of the leading advisers to the New Labour project, as ‘neither privileged nor deprived’.113 Steadily this group has been shrinking in size, eroded by ‘job polarisation’.114 The result is a country increasingly divided between the ‘privileged’ and the deprived’ with a much smaller group who are ‘neither’.


pages: 324 words: 92,805

The Impulse Society: America in the Age of Instant Gratification by Paul Roberts

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, American Society of Civil Engineers: Report Card, asset allocation, business process, Cass Sunstein, centre right, choice architecture, collateralized debt obligation, collective bargaining, computerized trading, corporate governance, corporate raider, corporate social responsibility, creative destruction, crony capitalism, David Brooks, delayed gratification, double helix, factory automation, financial deregulation, financial innovation, fixed income, full employment, game design, greed is good, If something cannot go on forever, it will stop - Herbert Stein's Law, impulse control, income inequality, inflation targeting, invisible hand, job automation, John Markoff, Joseph Schumpeter, knowledge worker, late fees, Long Term Capital Management, loss aversion, low skilled workers, mass immigration, new economy, Nicholas Carr, obamacare, Occupy movement, oil shale / tar sands, performance metric, postindustrial economy, profit maximization, Report Card for America’s Infrastructure, reshoring, Richard Thaler, rising living standards, Robert Shiller, Robert Shiller, Rodney Brooks, Ronald Reagan, shareholder value, Silicon Valley, speech recognition, Steve Jobs, technoutopianism, the built environment, The Predators' Ball, the scientific method, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, total factor productivity, Tyler Cowen: Great Stagnation, Walter Mischel, winner-take-all economy

In the United States, another six million manufacturing jobs, or a third of the total, went away between 2000 and 2007.11 Granted, we should not sentimentalize manufacturing jobs, which are often monotonous, dangerous, and unpleasant; many a factory worker would likely be glad to upgrade to something better. Nor, obviously, is there anything inherently wrong with automation or even offshoring. They are simply instruments of Schumpeter’s creative destruction: In “destroying” these older jobs in industrialized economies, automation and offshoring are, ideally, “creating” room for the next generation of jobs that will allow those displaced workers to step up the ladder to more productivity, better wages, and higher aspirations. Except that, under the Impulse Society, this is not what has happened. Displaced workers by and large have not stepped up to the next rung on the job ladder—or not in the numbers necessary to maintain the pattern of rising postwar prosperity.

Industry 4.0: The Industrial Internet of Things by Alasdair Gilchrist

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3D printing, additive manufacturing, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, business intelligence, business process, chief data officer, cloud computing, connected car, cyber-physical system, deindustrialization, fault tolerance, global value chain, Google Glasses, hiring and firing, industrial robot, inflight wifi, Infrastructure as a Service, Internet of things, inventory management, job automation, low skilled workers, millennium bug, pattern recognition, peer-to-peer, platform as a service, pre–internet, race to the bottom, RFID, Skype, smart cities, smart grid, smart meter, smart transportation, software as a service, stealth mode startup, supply-chain management, trade route, web application, WebRTC, WebSocket, Y2K

The digital transformation of operational processes can reap very early benefits, sometimes termed picking the low lying fruit, so it is an attractive initial area to focus on. Process Digitization The benefits of process digitization extend right through the value chain from early rapid development and prototyping of a product, to automated production lines and efficient stock control and dispatch. Automation of production line enables workers to be freed to do other less tedious repetitive jobs, such as supervising automated processes and using their production and product experience in a quality-control capacity. Digitizing processes also saves money as products and stock are more efficiently created and replenished using automatic stock replenishment procedures in ERP. Digitization facilitates a variety of stock handling and inventory controls, such as build-to-stock, build-to-order, or engineer-to-order.


pages: 375 words: 88,306

The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism by Arun Sundararajan

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3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, autonomous vehicles, barriers to entry, basic income, bitcoin, blockchain, Burning Man, call centre, collaborative consumption, collaborative economy, collective bargaining, commoditize, corporate social responsibility, cryptocurrency, David Graeber, distributed ledger, employer provided health coverage, Erik Brynjolfsson, ethereum blockchain, Frank Levy and Richard Murnane: The New Division of Labor, future of work, George Akerlof, gig economy, housing crisis, Howard Rheingold, information asymmetry, Internet of things, inventory management, invisible hand, job automation, job-hopping, Kickstarter, knowledge worker, Kula ring, Lyft, Marc Andreessen, megacity, minimum wage unemployment, moral hazard, moral panic, Network effects, new economy, Oculus Rift, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, peer-to-peer rental, profit motive, purchasing power parity, race to the bottom, recommendation engine, regulatory arbitrage, rent control, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Silicon Valley, smart contracts, Snapchat, social software, supply-chain management, TaskRabbit, The Nature of the Firm, total factor productivity, transaction costs, transportation-network company, two-sided market, Uber and Lyft, Uber for X, universal basic income, Zipcar

In a September 2015 Project Syndicate op-ed, my NYU Stern colleague and Nobel-prize winning economist Michael Spence summarized why: The truth is that the Internet-led process of exploiting under-utilized resources—be they physical and financial capital or human capital and talent—is both unstoppable and accelerating. The long-term benefits consist not just in efficiency and productivity gains (large enough to show up in macro data), but also in much-needed new jobs requiring a broad range of skills. Indeed, those who fear the job-destroying and job-shifting power of automation should look upon the sharing economy and breathe a bit of a sigh of relief.”1 *** The professor in me hopes that the book leaves you with a set of frameworks that give you new perspective, a critical lens through which you develop your own, deeper, understanding of this complex new world. (As Marcel Proust has told us, “The true voyage of discovery is not in seeking new landscapes but in having new eyes.”)


pages: 316 words: 90,165

pages: 265 words: 74,000

The Numerati by Stephen Baker

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Berlin Wall, Black Swan, business process, call centre, correlation does not imply causation, Drosophila, full employment, illegal immigration, index card, Isaac Newton, job automation, job satisfaction, McMansion, Myron Scholes, natural language processing, PageRank, personalized medicine, recommendation engine, RFID, Silicon Valley, Skype, statistical model, Watson beat the top human players on Jeopardy!

And late in 2007, according to the New York Times, the Chinese government announced plans not only to monitor the streets of the southern city of Shenzhen with 20,000 police cameras but also to give police there access to the feeds from another 180,000 video cameras run by the government and private companies. All of us, from bombers to subway passengers, will be playing ever bigger roles in these surveillance films. But on this global stage—unlike the cozy casinos in Las Vegas—there aren't nearly enough human workers to monitor all the action. And the machinery to sift through all this video isn't yet up to the job. At this point, an automated system can compare mug shots of suspects with thousands of photos on file, and suggest a handful of them that have a similar facial profile—before handing over the job to humans. Despite what Hollywood would have you believe, identifying faces in the real world is still very much a work in progress. Faces duck in and out of shadows. They turn from full face to profile. They tighten as we laugh and bulge as we eat.


pages: 271 words: 77,448

Humans Are Underrated: What High Achievers Know That Brilliant Machines Never Will by Geoff Colvin

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Ada Lovelace, autonomous vehicles, Baxter: Rethink Robotics, Black Swan, call centre, capital asset pricing model, commoditize, computer age, corporate governance, creative destruction, deskilling, en.wikipedia.org, Freestyle chess, future of work, Google Glasses, Grace Hopper, industrial cluster, industrial robot, interchangeable parts, job automation, knowledge worker, low skilled workers, Marc Andreessen, meta analysis, meta-analysis, Narrative Science, new economy, rising living standards, self-driving car, sentiment analysis, Silicon Valley, Skype, Steve Jobs, Steve Wozniak, Steven Levy, Steven Pinker, theory of mind, Tim Cook: Apple, transaction costs

In a significant lecture to an audience of fellow economists, he summarized in his brisk way the orthodox view of the debate over technology: “There were the stupid Luddite people, who mostly were outside of economics departments, and there were the smart progressive people. . . . The stupid people thought that automation was going to make all the jobs go away and there wasn’t going to be any work to do. And the smart people understood that when more was produced, there would be more income and therefore there would be more demand. It wasn’t possible that all the jobs would go away, so automation was a blessing.” Evidence overwhelmingly supported that view for decades. All you had to do was imagine the world of 1800 and compare it with the world around you. But then, quite recently, the world changed: “Until a few years ago, I didn’t think this was a very complicated subject,” Summers said. “The Luddites were wrong and the believers in technology and technological progress were right.


pages: 288 words: 66,996

Travel While You Work: The Ultimate Guide to Running a Business From Anywhere by Mish Slade

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Airbnb, Atul Gawande, business process, Checklist Manifesto, cloud computing, crowdsourcing, Firefox, Google Chrome, Google Hangouts, Inbox Zero, job automation, Lyft, remote working, side project, Skype, speech recognition, turn-by-turn navigation

I will break some of these rules of thumb if someone contacts me with a particularly engaging application and seems to have a firm grasp of what's required of them. One more tip: somewhere in your job description, ask the candidates to tell you something random about themselves. In the past I've asked them to tell me their favourite type of cheese, their favourite animal at the zoo, and their shoe size. It's a simple way to filter out those candidates who either haven't read the job properly or are using automated software to bid for jobs. I also like it because it's nice to work with people who have a sense of humour, and some of the responses I receive are hilarious! Hourly or fixed price? You usually have the option to specify whether you want to pay your contractor an hourly rate or a fixed price. While it's kind of "totally up to you" and no one's going to put you in prison for choosing one over the other, it's not really totally up to you – not if you want to hire in a way that best suits your needs.


pages: 165 words: 47,320

The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling by Ralph Kimball, Margy Ross

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active measures, Albert Einstein, business intelligence, business process, call centre, cloud computing, data acquisition, discrete time, inventory management, iterative process, job automation, knowledge worker, performance metric, platform as a service, side project, supply-chain management, zero-sum game

See HR (human resources), 263 hybrid hub-and-spoke Kimball architecture, 29 hybrid techniques, SCDs, 159, 164 SCD type 5 (add mini-dimension and type 1 outrigger), 55, 160 SCD type 6 (add type 1 attributes to type 2 dimension), 56, 160–162 SCD type 7 (dual type 1 and type 2 dimension), 56, 162–163 hyperstructured data, 530 I ICD (International Classification of Diseases), 342 identical conformed dimensions, 131–132 images, healthcare case study, 350 impact reports, 288 incremental processing, ETL system development, 512 changed dimension rows, 513–514 dimension attribute changes, 514 dimension table extracts, 513 fact tables, 515–519 new dimension rows, 513–514 in-database analytics, big data and, 537 independent data mart architecture, 26–27 indicators abnormal, fact tables, 255–256 as textual attributes, 48 dimension tables, 82 junk dimensions and, 179–180 satisfaction, fact tables, 254–255 Inmon, Bill, 28–29 insurance case study, 375–377 accidents, factless fact tables, 396 accumulating snapshot, complementary policy, 384–385 bus matrix, 378–389 detailed implementation, 390 claim transactions, 390 claim accumulating snapshot, 393–394 junk dimensions and, 392 periodic snapshot, 395–396 timespan accumulating snapshot, 394–395 conformed dimensions, 386 conformed facts, 386 dimensions, 380 audit, 383 degenerate, 383 low cardinality, 383 mini-dimensions, 381–382 multivalued, 382, 388 SCDs (slowly changing dimensions), 380–381 NAICS (North American Industry Classification System), 382 numeric attributes, 382 pay-in-advance facts, 386–387 periodic snapshot, 385 policy transactions, 379–380, 383 premiums, periodic snapshot, 386–388 SIC (Standard Industry Classification), 382 supertype/subtype products, 384, 387 value chain, 377–378 integer keys, 98 sequential surrogate keys, 101 Index integration conformed dimensions, 130–138 customer data, 256 customer dimension conformity, 258–259 single customer dimension, 256, 257, 258 dimensional modeling myths, 32 value chain, 122–123 international names/addresses, customer dimension, 236–238 interviews, Lifecycle business requirements, 412–413 data-centric, 413–414 inventory case study, 112–114 accumulating snapshot, 118–119 fact tables, enhanced, 115–116 periodic snapshot, 112–114 semi-additive facts, 114–115 transactions, 116–118 inventory, healthcare case study, 351 invoice transaction fact table, 187–188 J job scheduler, ETL systems, 483–484 job scheduling, ETL operation and automation, 520 joins dimension-to-dimension table joins, 62 fact tables, avoiding, 259–260 many-to-one-to-many, 259–260 multipass SQL to avoid fact-to-fact joins, 61 journal entries (G/L), 206–207 junk dimensions, 49, 179–180, 284 airline case study, 320 ETL systems, 470 insurance case study, 392 order management case study, 179–180 justification for program/project planning, 407 K keys dimension surrogate keys, 46 durable, 46 foreign, 92, 291 managers key (HR), 272–273 natural keys, 46, 98–101, 162 supernatural keys, 101 smart keys, 101–102 subtype tables, 294–295 supernatural, 46 supertype tables, 294–295 surrogate, 58, 98–100, 303 assigning, 506 degenerate dimensions, 101 557 ETL system, 475–477 fact tables, 102–103 generator, 469–470 lookup pipelining, 510–511 keywords, skill keywords, 274 bridge, 275 text string, 276–277 Kimball Dimensional Modeling Techniques.

See dimensional modeling Kimball DW/BI architecture, 18 BI applications, 22 ETL (extract, transformation, and load) system, 19–21 hub-and-spoke hybrid, 29 presentation area, 21–22 restaurant metaphor, 23–26 source systems, operational source systems, 18 Kimball Lifecycle, 404 DW/BI initiative and, 404 KPIs (key performance indicators), 139 L lag calculations, 196–197 lag/duration facts, 59 late arriving data handler, ETL system, 478–479 late arriving dimensions, 67 late arriving facts, 62 launch, Lifecycle business requirements, 412 Law of Too, 407 legacy environments, big data management, 532 legacy licenses, ETL system, 449 Lifecycle BI applications, 406 development, 423–424 specification, 423 business requirements, 405, 410 documentation, 414 forum selection, 410–411 interviews, 412–413 interviews, data-centric, 413–414 launch, 412 prioritization, 414–415 representatives, 411–412 team, 411 data, 405 dimensional modeling, 420 ETL design/development, 422 physical design, 420–422 deployment, 424 growth, 425–426 maintenance, 425–426 pitfalls, 426 558 Index products evaluation matrix, 419 market research, 419 protoypes, 419 program/project planning, 405–406 business motivation, 407 business sponsor, 406 development, 409–410 feasibility, 407 justification, 407 planning, 409–410 readiness assessment, 406–407 scoping, 407 staffing, 408–409 technical architecture, 405, 416–417 implementation phases, 418 model creation, 417 plan creation, 418 requirements, 417 requirements collection, 417 subsystems, 418 task force, 417 lift, promotion, 89 lights-out operations, backup, 485 limited conformed dimensions, 135 lineage analysis, 495 lineage, ETL system, 447–448, 490–491 loading fact tables, incremental, 517 localization, 237, 324 location, geographic location dimension, 310 log scraping, CDC (change data capture), 453 low cardinality dimensions, insurance case study, 383 low latency data, CRM and, 260–261 M maintenance, Lifecycle, 425–426 management ETL systems, 450, 483 backup system, 485–495 job scheduler, 483–484 management best practices, big data analytics, 531 legacy environments, 532 sandbox results, 532–533 sunsetting and, 533 management hierarchies, drilling up/down, 273–274 managers, publishing metaphor, 5–7 many-to-one hierarchies, 84–85 many-to-one relationships, 175–176 many-to-one-to-many joins, 259–260 MapReduce/Hadoop, 530 market growth, 90 master dimensions, 130 MDM (master data management), 137, 256, 446 meaningless keys, 98 measurement, multiple, 61 measure type dimension, 65 healthcare case study, 349–350 message queue monitoring, CDC (change data capture), 453 metadata coordinator, 409 metadata repository, ETL system, 495 migration, version migration system, ETL, 488 milestones, accumulating snapshots, 121 mini-dimension and type 1 outrigger (SCD type 5), 160 mini-dimensions, 289–290 bridge tables, 290–291 ETL systems, 471 insurance case study, 381–382 type 4 SCD, 156–159 modeling benefits of thinking dimensionally, 32–33 dimensional, 7–12 atomic grain data, 17 dimension tables, 13–15 extensibility, 16 myths, 30–32 reports, 17 simplicity in, 16 terminology, 15 multipass SQL, avoiding fact-to-fact table joins, 61 multiple customer dimension, partial conformity, 258–259 multiple units of measure, 61, 197–198 multivalued bridge tables CRM and, 245–246 time varying, 63 multivalued dimensions bridge table builder, 477–478 bridge tables and, 63 CRM and, 245–247 education case study, 325–333 financial services case study, 287–289 healthcare case study, 345–348 HR (human resources) case study, 274–275 insurance case study, 382–388 weighting factors, 287–289 myths about dimensional modeling, 30 departmental versus enterprise, 31 integration, 32 predictable use, 31–32 scalability, 31 summary data, 30 Index N names ASCII, 236 CRM and, customer dimension, 233–238 Unicode, 236–238 name-value pairs, 540 naming conventions, 433 natural keys, 46, 98–101, 162 supernatural keys, 101 NCOA (national change of address), 257 nodes (hierarchies), 215 non-additive facts, 42, 78 non-natural keys, 98 normalization, 28, 301 facts centipede, 108–109 order transactions, 169–170 outriggers, 106–107 snowflaking, 104–106 normalized 3NF structures, 8 null attributes, 48 null fact values, 509 null values fact tables, 42 foreign keys, 92 number attributes, insurance case study, 382 numeric facts, 11 numeric values as attributes, 59, 85–86 as facts, 59, 85–86 O off-invoice allowance (P&L) statement, 190 OLAP (online analytical processing) cube, 8, 40 accounting case study, 226 accumulating snapshots, 121–122 aggregate, 45 cube builder, ETL system, 481–482 deployment considerations, 9 employee data queries, 273 financial schemas, 226 Lifecycle data physical design, 421 loads, ETL system, 519 what didn’t happen, 335 one-to-one relationships, 175–176 operational processing versus data warehousing, 2 operational product master, product dimensions, 173 operational source systems, 18 operational system users, 2 opportunity/stakeholder matrix, 53, 127 order management case study, 167–168 559 accumulating snapshot, 194–196 type 2 dimensions and, 196 allocating, 184–186 audit dimension, 192–193 bus matrix, 168 currency, multiple, 182–184 customer dimension, 174–175 factless fact tables, 176 single versus multiple dimension tables, 175–176 date, 170–171 foreign keys, 170 role playing, 171 deal dimension, 177–178 degenerate dimension, order number and, 178–179 fact normalization, 169–170 header/line patterns, 181–186 junk dimensions, 179–180 product dimension, 172–173 order number, degenerate dimensions, 178–179 order management case study, role playing, 171 origin dimension (airline case study), 320–321 OR, skill keywords bridge, 275 outrigger dimensions, 50, 89, 106–107 calendars as, 321–323 low cardinality attribute set and, 243–244 type 5 and type 1 SCD, 160 overwrite (type 1 SCD), 54, 149–150 add to type 2 attribute, 160–162 type 2 in same dimension, 153 P packaged analytic solutions, 270–271 packaged data models, 270–271 page dimension, clickstream data, 358–359 page event fact table, clickstream data, 363–366 parallelizing/pipelining system, 492 parallel processing, fact tables, 518 parallel structures, fact tables, 519 parent/child schemas, 59 parent/child tree structure hierarchy, 216 partitioning fact tables, smart keys, 102 real-time processing, 524–525 passenger dimension, airline case study, 314 pathstring, ragged/variable depth hierarches, 57 pay-in-advance facts, insurance case study, 386–387 payment method, retail sales, 93 560 Index performance measurement, fact tables, 10, 12 additive facts, 11 grains, 10–12 numeric facts, 11 textual facts, 12 period close (G/L), 204–206 periodic snapshots, 43, 112–114 education case study, 329, 333 ETL systems, 474 fact tables, 120–121 complementary fact tables, 122 G/L (general ledger), 203 grain fact tables, 12 headcount, 267–268 healthcare case study, 342 insurance case study, 385 claims, 395–396 premiums, 386–387 inventory case study, 112–114 procurement case study, 147 perspectives of business users, 293 physical design, Lifecycle data track, 420 aggregations, 421 database model, 421 database standards, 420 index plan, 421 naming standards, 420–421 OLAP database, 421 storage, 422 pipelining system, 492 planning, demand planning, 142 P&L (profit and loss) statement contribution, 189–191 granularity, 191–192 policy transactions (insurance case study), 379–380 fact table, 383 PO (purchase orders), 142 POS (point-of-sale) system, 73 POS schema, retail sales case study, 94 transaction numbers, 93–94 presentation area, 21–22 prioritization, Lifecycle business requirements, 414–415 privacy, data governance and, 541–542 problem escalation system, 491–492 procurement case study, 141–142 bus matrix, 142–143 snapshot fact table, 147 transactions, 142–145 product dimension, 83–84 attributes with embedded meaning, 85 characteristics, 172–173 drilling down, 86–87 many-to-one hierarchies, 84–85 numeric values, 85–86 operational product master, 173 order transactions, 172–173 operational product master, 173 production codes, decoding, 504 products heterogeneous, 293–295 Lifecycle evaluation matrix, 419 market research, 419 prototypes, 419 profit and loss facts, 189–191, 370–372 allocations and, 60 granularity, 191–192 program/project planning (Lifecycle), 405–406 business motivation, 407 business sponsor, 406 development, 409–410 feasibility, 407 justification, 407 planning, 409–410 readiness assessment, 406–407 scoping, 407 staffing, 408–409 task list, 409 project manager, 409 promotion dimension, 89–91 null values, 92 promotion lift, 89 prototypes big data and, 536 Lifecycle, 419 publishing metaphor for DW/BI managers, 5–7 Q quality events, responses, 458 quality screens, ETL systems, 457–458 questionnaire, HR (human resources), 277 text comments, 278 R ragged hierarchies alternative modeling approaches, 221–223 bridge table approach, 223 modifying, 220–221 pathstring attributes, 57 shared ownership, 219 time varying, 220 variable depth, 215–217 rapidly changing monster dimension, 55 Index RDBMS (relational database management system), 40 architecture extension, 529–530 blobs, 530 fact extractor, 530 hyperstructured data, 530 real-time fact tables, 68 real-time processing, 520–522 architecture, 522–524 partitions, 524–525 rearview mirror metrics, 198 recovery and restart system, ETL system, 486–488 recursive hierarchies, employees, 271–272 reference dimensions, 130 referential integrity, 12 referral dimension, clickstream data, 360 relationships dimension tables, 15 many-to-one, 175–176 many-to-one-to-many joins, 259–260 one-to-one, 175–176 validation, 504–505 relative date attributes, 82–83 remodeling existing data structures, 309 reports correctly weighted, 288 dimensional models, 17 dynamic value banding, 64 fact tables, 17 impact, 288 value band reporting, 291–292 requirements for dimensional modeling, 432 restaurant metaphor for Kimball architecture, 23–26 retail sales case study, 72–73, 92 business process selection, 74 dimensions, selecting, 76 facts, 76–77 derived, 77–78 non-additive, 78 fact tables, 79 frequent shopper program, 96 grain declaration, 74–75 payment method, 93 POS (point-of-sale) system, 73 POS schema, 94 retail schema extensibility, 95–97 SKUs, 73 retain original (SCD type 0), 54, 148–149 retrieval, 485–486 retroactive changes, healthcare case study, 351–352 reviewing dimensional model, 440, 441 RFI measures, 240 561 RFP (request for proposal), 419 role playing, dimensions, 49, 89, 171, 284 airline case study, 313 bus matrix and, 171 healthcare case study, 345 insurance case study, 380 order management case study, 170 S sales channel dimension, airline case study, 315 sales reps, factless fact tables, 176 sales transactions, web profitability and, 370–372 sandbox results, big data management, 532–533 sandbox source system, ETL development, 503 satisfaction indicators in fact tables, 254–255 scalability, dimensional modeling myths, 31 SCDs (slowly changing dimensions), 53, 148, 464–465 big data and, 539 detailed dimension model, 437 hybrid techniques, 159–164 insurance case study, 380–381 type 0 (retain original), 54, 148–149 type 1 (overwrite), 54, 149–150 ETL systems, 465 type 2 in same dimension, 153 type 2 (add new row), 54, 150–152 accumulating snapshots, 196 customer counts, 243 effective date, 152–153 ETL systems, 465–466 expiration date, 152–153 type 1 in same dimension, 153 type 3 (add new attribute), 55, 154–155 ETL systems, 467 multiple, 156 type 4 (add mini-dimension), 55, 156–159 ETL systems, 467 type 5 (add mini-dimension and type 1 outrigger), 55, 160 ETL systems, 468 type 6 (add type 1 attributes to type 2 dimension), 56, 160–162 ETL systems, 468 type 7 (dual type 1 and type 2 dimension), 56, 162–164 ETL systems, 468 scheduling jobs, ETL operation and automation, 520 scoping for program/project planning, 407 562 Index scoring, CRM and customer dimension, 240–243 screening ETL systems business rule screens, 458 column screens, 457 structure screens, 457 quality screens, 457–458 security, 495 ETL system, 446, 492–493 goals, 4 segmentation, CRM and customer dimension, 240–243 segments, airline bus matrix granularity, 313 linking to trips, 315–316 SELECT statement, 18 semi-additive facts, 42, 114–115 sequential behavior, step dimension, 65, 251–252 sequential integers, surrogate keys, 101 service level performance, 188–189 session dimension, clickstream data, 359–360 session fact table, clickstream data, 361–363 session IDs, clickstream data, 355–356 set difference, 97 shared dimensions, 130 shipment invoice fact table, 188 shrunken dimensions, 51 conformed attribute subset, 132 on bus matrix, 134 row subsets and, 132–134 rollup, 132 subsets, ETL systems, 472 simple administration backup, 485 simple data transformation, dimensions, 504 single customer dimension, data integration and, 256–258 single granularity, facts and, 301 single version of the truth, 407 skill keywords, 274 bridge, 275 AND queries, 275 OR queries, 275 text string, 276–277 skills, ETL system, 448 SKUs (stock keeping units), 73 slightly ragged/variable depth hierarchies, 57 slowly changing dimensions.


pages: 372 words: 67,140

pages: 221 words: 68,880

Bikenomics: How Bicycling Can Save the Economy (Bicycle) by Elly Blue

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, active transport: walking or cycling, American Society of Civil Engineers: Report Card, big-box store, car-free, hydraulic fracturing, if you build it, they will come, Induced demand, Jane Jacobs, job automation, Loma Prieta earthquake, medical residency, oil shale / tar sands, peak oil, Ponzi scheme, ride hailing / ride sharing, science of happiness, the built environment, urban renewal, women in the workforce, working poor, young professional

A university staffer told me that they had replaced their small fleet of pickup trucks with these bicycles, which did the job just as well and provided a safer and quieter environment for students. Most bike-based businesses are by nature small or medium-sized. With their low overhead and replacement of fuel with human power, they provide something that is sorely needed right now—jobs. Bike delivery can’t be automated or outsourced—you need a human being, hauling a human-scaled load all over town to make these operations work. When places thrive, people and goods simply don’t have to travel as far. Laura Crawford and Russ Roca, on the other hand, choose to go on long bicycle trips and can bring their work with them. They went on their first bike tour in 2009, pedaling through the desert in Joshua Tree National Park with camping gear, food, and water strapped to their racks.


pages: 309 words: 91,581

The Great Divergence: America's Growing Inequality Crisis and What We Can Do About It by Timothy Noah

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assortative mating, autonomous vehicles, blue-collar work, Bonfire of the Vanities, Branko Milanovic, call centre, collective bargaining, computer age, corporate governance, Credit Default Swap, David Ricardo: comparative advantage, Deng Xiaoping, Erik Brynjolfsson, feminist movement, Frank Levy and Richard Murnane: The New Division of Labor, Gini coefficient, Gunnar Myrdal, income inequality, industrial robot, invisible hand, job automation, Joseph Schumpeter, low skilled workers, lump of labour, manufacturing employment, moral hazard, oil shock, pattern recognition, Paul Samuelson, performance metric, positional goods, post-industrial society, postindustrial economy, Powell Memorandum, purchasing power parity, refrigerator car, rent control, Richard Feynman, Richard Feynman, Ronald Reagan, shareholder value, Silicon Valley, Simon Kuznets, Stephen Hawking, Steve Jobs, The Spirit Level, too big to fail, trickle-down economics, Tyler Cowen: Great Stagnation, union organizing, upwardly mobile, very high income, Vilfredo Pareto, War on Poverty, We are the 99%, women in the workforce, Works Progress Administration, Yom Kippur War

Between 1980 and 2005, service jobs’ share of U.S. labor hours increased by 30 percent, according to a 2011 paper by Autor and David Dorn, an assistant professor of economics at the Center for Monetary and Financial Studies in Madrid. Among workers with no more than a high school education, service jobs’ share of U.S. labor hours increased by more than half. During the three decades prior to the Great Divergence, these lower-wage service jobs’ share of labor hours had either declined or stayed flat. Autor and Dorn’s bottom line is that as moderately skilled workers’ jobs were wiped out by automation they were pushed into lower-paid service jobs that computers can’t perform but that people can.13 Autor and Dorn’s bleak view of middle-class decline is challenged in Where Are All the Good Jobs Going?, a 2011 book by the Georgetown economist Harry Holzer in collaboration with Julia Lane, David Rosenblum, and Fredrik Andersson (economists at, respectively, the National Science Foundation, the University of Chicago’s National Opinion Research Center, and the U.S.


pages: 366 words: 94,209

Throwing Rocks at the Google Bus: How Growth Became the Enemy of Prosperity by Douglas Rushkoff

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3D printing, activist fund / activist shareholder / activist investor, Airbnb, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, bank run, banking crisis, barriers to entry, bitcoin, blockchain, Burning Man, business process, buy low sell high, California gold rush, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, centralized clearinghouse, citizen journalism, clean water, cloud computing, collaborative economy, collective bargaining, colonial exploitation, Community Supported Agriculture, corporate personhood, corporate raider, creative destruction, crowdsourcing, cryptocurrency, disintermediation, diversified portfolio, Elon Musk, Erik Brynjolfsson, ethereum blockchain, fiat currency, Firefox, Flash crash, full employment, future of work, gig economy, Gini coefficient, global supply chain, global village, Google bus, Howard Rheingold, IBM and the Holocaust, impulse control, income inequality, index fund, iterative process, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joseph Schumpeter, Kickstarter, loss aversion, Lyft, Marc Andreessen, Mark Zuckerberg, market bubble, market fundamentalism, Marshall McLuhan, means of production, medical bankruptcy, minimum viable product, Naomi Klein, Network effects, new economy, Norbert Wiener, Oculus Rift, passive investing, payday loans, peer-to-peer lending, Peter Thiel, post-industrial society, profit motive, quantitative easing, race to the bottom, recommendation engine, reserve currency, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Snapchat, social graph, software patent, Steve Jobs, TaskRabbit, The Future of Employment, trade route, transportation-network company, Turing test, Uber and Lyft, Uber for X, unpaid internship, Y Combinator, young professional, zero-sum game, Zipcar

The higher-skilled staff jobs were replaced with unskilled labor putting DVDs in mailers. When the company became a streaming service, even those unskilled jobs were eliminated. It’s as if whenever we start down the path of trying to find an employment solution for people in a digital landscape, we end up in the same defenseless, jobless place. We can’t get paid for our cultural product unless we’re one of the Top 10 artists of the year. We can’t get good at any job skill without its being automated by someone with a free smartphone app. The more time and assets we can get on the books, the faster they are devalued or replaced by a new technology. More than two thirds of job losses are now the direct result of having one’s function taken over by a machine. So far, these are mostly middle-class jobs, such as manufacturing, office assistance, and calculating. Commonsense advice to replaced workers was always for them to retrain and learn higher-level skills.


pages: 326 words: 103,170

The Seventh Sense: Power, Fortune, and Survival in the Age of Networks by Joshua Cooper Ramo

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Airbnb, Albert Einstein, algorithmic trading, barriers to entry, Berlin Wall, bitcoin, British Empire, cloud computing, crowdsourcing, Danny Hillis, defense in depth, Deng Xiaoping, drone strike, Edward Snowden, Fall of the Berlin Wall, Firefox, Google Chrome, income inequality, Isaac Newton, Jeff Bezos, job automation, market bubble, Menlo Park, Metcalfe’s law, natural language processing, Network effects, Norbert Wiener, Oculus Rift, packet switching, Paul Graham, price stability, quantitative easing, RAND corporation, recommendation engine, Republic of Letters, Richard Feynman, Richard Feynman, road to serfdom, Robert Metcalfe, Sand Hill Road, secular stagnation, self-driving car, Silicon Valley, Skype, Snapchat, social web, sovereign wealth fund, Steve Jobs, Steve Wozniak, Stewart Brand, Stuxnet, superintelligent machines, technological singularity, The Coming Technological Singularity, The Wealth of Nations by Adam Smith, too big to fail, Vernor Vinge, zero day

But the design of capital markets at the time of the 2008 crisis ensured that most of the benefits of a loose monetary policy accumulated to those who already had money. (Among other reasons, because they were connected to networks of credit, investment, and information that elude most citizens.) At the same time, new technology and networks of trade, finance, and information meant that middle-class jobs were being exported or automated. So the once prosperous middle class, an essential element of any stable capitalist system, was being pulled apart. The rich were getting richer; the poor in other countries (or the machines) were taking the jobs. Though financial and monetary stimulus were pouring into the system, there was no trickle down. “The extent and continuing increase in income inequality in the United States greatly concern me,” Bernanke’s successor Janet Yellen remarked in 2015, after seven years of quantitative easing policy.


pages: 283 words: 85,824

The People's Platform: Taking Back Power and Culture in the Digital Age by Astra Taylor

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A Declaration of the Independence of Cyberspace, American Legislative Exchange Council, Andrew Keen, barriers to entry, Berlin Wall, big-box store, Brewster Kahle, citizen journalism, cloud computing, collateralized debt obligation, Community Supported Agriculture, conceptual framework, corporate social responsibility, creative destruction, cross-subsidies, crowdsourcing, David Brooks, digital Maoism, disintermediation, don't be evil, Donald Trump, Edward Snowden, Fall of the Berlin Wall, Filter Bubble, future of journalism, George Gilder, Google Chrome, Google Glasses, hive mind, income inequality, informal economy, Internet Archive, Internet of things, invisible hand, Jane Jacobs, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Julian Assange, Kevin Kelly, Kickstarter, knowledge worker, Mark Zuckerberg, means of production, Metcalfe’s law, Naomi Klein, Narrative Science, Network effects, new economy, New Journalism, New Urbanism, Nicholas Carr, oil rush, peer-to-peer, Peter Thiel, Plutocrats, plutocrats, pre–internet, profit motive, recommendation engine, Richard Florida, Richard Stallman, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, slashdot, Slavoj Žižek, Snapchat, social graph, Steve Jobs, Stewart Brand, technoutopianism, trade route, Whole Earth Catalog, WikiLeaks, winner-take-all economy, Works Progress Administration, young professional

The advances of technology did not, in the end, liberate the worker from drudgery but rather further empowered those who owned the machines. By the end of the 1970s, as former labor secretary Robert Reich explains, a wave of new technologies (air cargo, container ships and terminals, satellite communications and, later, the Internet) had radically reduced the costs of outsourcing jobs abroad. Other new technologies (automated machinery, computers, and ever more sophisticated software applications) took over many other jobs (remember bank tellers? telephone operators? service station attendants?). By the ’80s, any job requiring that the same steps be performed repeatedly was disappearing—going over there or into software.25 At the same time the ideal of a “postindustrial society” offered the alluring promise of work in a world in which goods were less important than services.


pages: 761 words: 80,914

Ansible: Up and Running: Automating Configuration Management and Deployment the Easy Way by Lorin Hochstein

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Amazon Web Services, cloud computing, continuous integration, Debian, DevOps, domain-specific language, don't repeat yourself, general-purpose programming language, Infrastructure as a Service, job automation, pull request, side project, smart transportation, web application

In the next one, we’ll discuss roles, a convenient mechanism for organizing your playbooks. 1 Thanks to John Jarvis for this tip. 2 Don’t Repeat Yourself, a term popularized by The Pragmatic Programmer: From Journeyman to Master, which is a fantastic book. 3 etcd is a distributed key-value store, and is maintained by the CoreOS project. 4 If this sounds like gibberish, don’t worry about it; it’s just an example of running a command. 5 DNS service providers typically have web interfaces to let you perform DNS-related tasks such as creating TXT records. Chapter 8. Roles: Scaling Up Your Playbooks One of the things I like about Ansible is how it scales both up and down. I’m not referring to the number of hosts you’re managing, but rather the complexity of the jobs you’re trying to automate. Ansible scales down well because simple tasks are easy to implement. It scales up well because it provides mechanisms for decomposing complex jobs into smaller pieces. In Ansible, the role is the primary mechanism for breaking apart a playbook into multiple files. This simplifies writing complex playbooks, and it also makes them easier to reuse. Think of a role as something you assign to one or more hosts.


pages: 443 words: 98,113

The Corruption of Capitalism: Why Rentiers Thrive and Work Does Not Pay by Guy Standing

3D printing, Airbnb, Albert Einstein, Amazon Mechanical Turk, Asian financial crisis, asset-backed security, bank run, banking crisis, basic income, Ben Bernanke: helicopter money, Bernie Sanders, Big bang: deregulation of the City of London, bilateral investment treaty, Bonfire of the Vanities, Bretton Woods, Capital in the Twenty-First Century by Thomas Piketty, carried interest, cashless society, central bank independence, centre right, Clayton Christensen, collapse of Lehman Brothers, collective bargaining, credit crunch, crony capitalism, crowdsourcing, debt deflation, declining real wages, deindustrialization, Doha Development Round, Donald Trump, Double Irish / Dutch Sandwich, ending welfare as we know it, eurozone crisis, falling living standards, financial deregulation, financial innovation, Firefox, first-past-the-post, future of work, gig economy, Goldman Sachs: Vampire Squid, Growth in a Time of Debt, housing crisis, income inequality, information retrieval, intangible asset, invention of the steam engine, investor state dispute settlement, James Watt: steam engine, job automation, John Maynard Keynes: technological unemployment, labour market flexibility, light touch regulation, Long Term Capital Management, lump of labour, Lyft, manufacturing employment, Mark Zuckerberg, market clearing, Martin Wolf, means of production, mini-job, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, Neil Kinnock, non-tariff barriers, North Sea oil, Northern Rock, nudge unit, Occupy movement, offshore financial centre, oil shale / tar sands, open economy, openstreetmap, patent troll, payday loans, peer-to-peer lending, Plutocrats, plutocrats, Ponzi scheme, precariat, quantitative easing, remote working, rent control, rent-seeking, ride hailing / ride sharing, Right to Buy, Robert Gordon, Ronald Coase, Ronald Reagan, savings glut, Second Machine Age, secular stagnation, sharing economy, Silicon Valley, Silicon Valley startup, Simon Kuznets, sovereign wealth fund, Stephen Hawking, Steve Ballmer, structural adjustment programs, TaskRabbit, The Chicago School, The Future of Employment, the payments system, Thomas Malthus, Thorstein Veblen, too big to fail, Uber and Lyft, Uber for X, Y Combinator, zero-sum game, Zipcar


pages: 603 words: 141,814

pages: 481 words: 120,693

Plutocrats: The Rise of the New Global Super-Rich and the Fall of Everyone Else by Chrystia Freeland

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activist fund / activist shareholder / activist investor, Albert Einstein, algorithmic trading, assortative mating, banking crisis, barriers to entry, Basel III, battle of ideas, Bernie Madoff, Big bang: deregulation of the City of London, Black Swan, Branko Milanovic, Bretton Woods, BRICs, business climate, call centre, carried interest, Cass Sunstein, Clayton Christensen, collapse of Lehman Brothers, commoditize, conceptual framework, corporate governance, creative destruction, credit crunch, Credit Default Swap, crony capitalism, Deng Xiaoping, don't be evil, double helix, energy security, estate planning, experimental subject, financial deregulation, financial innovation, Flash crash, Frank Gehry, Gini coefficient, global village, Goldman Sachs: Vampire Squid, Gordon Gekko, Guggenheim Bilbao, haute couture, high net worth, income inequality, invention of the steam engine, job automation, John Markoff, joint-stock company, Joseph Schumpeter, knowledge economy, knowledge worker, liberation theology, light touch regulation, linear programming, London Whale, low skilled workers, manufacturing employment, Mark Zuckerberg, Martin Wolf, Mikhail Gorbachev, Moneyball by Michael Lewis explains big data, NetJets, new economy, Occupy movement, open economy, Peter Thiel, place-making, Plutocrats, plutocrats, Plutonomy: Buying Luxury, Explaining Global Imbalances, postindustrial economy, Potemkin village, profit motive, purchasing power parity, race to the bottom, rent-seeking, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, self-driving car, short selling, Silicon Valley, Silicon Valley startup, Simon Kuznets, Solar eclipse in 1919, sovereign wealth fund, stem cell, Steve Jobs, the new new thing, The Spirit Level, The Wealth of Nations by Adam Smith, Tony Hsieh, too big to fail, trade route, trickle-down economics, Tyler Cowen: Great Stagnation, wage slave, Washington Consensus, winner-take-all economy, zero-sum game


pages: 504 words: 143,303

Why We Can't Afford the Rich by Andrew Sayer

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accounting loophole / creative accounting, Albert Einstein, asset-backed security, banking crisis, banks create money, basic income, Bretton Woods, British Empire, call centre, capital controls, carbon footprint, collective bargaining, corporate raider, corporate social responsibility, creative destruction, credit crunch, Credit Default Swap, crony capitalism, David Graeber, David Ricardo: comparative advantage, debt deflation, decarbonisation, declining real wages, deglobalization, deindustrialization, delayed gratification, demand response, don't be evil, Double Irish / Dutch Sandwich, en.wikipedia.org, Etonian, financial innovation, financial intermediation, Fractional reserve banking, full employment, G4S, Goldman Sachs: Vampire Squid, high net worth, income inequality, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), investor state dispute settlement, Isaac Newton, James Dyson, job automation, Julian Assange, labour market flexibility, laissez-faire capitalism, land value tax, low skilled workers, Mark Zuckerberg, market fundamentalism, Martin Wolf, mass immigration, means of production, moral hazard, mortgage debt, negative equity, neoliberal agenda, new economy, New Urbanism, Northern Rock, Occupy movement, offshore financial centre, oil shale / tar sands, patent troll, payday loans, Philip Mirowski, Plutocrats, plutocrats, popular capitalism, predatory finance, price stability, pushing on a string, quantitative easing, race to the bottom, rent-seeking, Ronald Reagan, shareholder value, short selling, sovereign wealth fund, Steve Jobs, The Nature of the Firm, The Spirit Level, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, transfer pricing, trickle-down economics, universal basic income, unpaid internship, upwardly mobile, Washington Consensus, wealth creators, Winter of Discontent, working poor, Yom Kippur War, zero-sum game


pages: 514 words: 152,903


pages: 1,104 words: 302,176

The Rise and Fall of American Growth: The U.S. Standard of Living Since the Civil War (The Princeton Economic History of the Western World) by Robert J. Gordon

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3D printing, Affordable Care Act / Obamacare, airline deregulation, airport security, Apple II, barriers to entry, big-box store, blue-collar work, Capital in the Twenty-First Century by Thomas Piketty, clean water, collective bargaining, computer age, creative destruction, deindustrialization, Detroit bankruptcy, discovery of penicillin, Donner party, Downton Abbey, Edward Glaeser, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, feminist movement, financial innovation, full employment, George Akerlof, germ theory of disease, glass ceiling, high net worth, housing crisis, immigration reform, impulse control, income inequality, income per capita, indoor plumbing, industrial robot, inflight wifi, interchangeable parts, invention of agriculture, invention of air conditioning, invention of the telegraph, invention of the telephone, inventory management, James Watt: steam engine, Jeff Bezos, jitney, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, labor-force participation, Loma Prieta earthquake, Louis Daguerre, Louis Pasteur, low skilled workers, manufacturing employment, Mark Zuckerberg, market fragmentation, Mason jar, mass immigration, mass incarceration, McMansion, Menlo Park, minimum wage unemployment, mortgage debt, mortgage tax deduction, new economy, Norbert Wiener, obamacare, occupational segregation, oil shale / tar sands, oil shock, payday loans, Peter Thiel, pink-collar, Productivity paradox, Ralph Nader, Ralph Waldo Emerson, refrigerator car, rent control, Robert X Cringely, Ronald Coase, school choice, Second Machine Age, secular stagnation, Skype, stem cell, Steve Jobs, Steve Wozniak, Steven Pinker, The Market for Lemons, Thomas Malthus, total factor productivity, transaction costs, transcontinental railway, traveling salesman, Triangle Shirtwaist Factory, Unsafe at Any Speed, Upton Sinclair, upwardly mobile, urban decay, urban planning, urban sprawl, washing machines reduced drudgery, Washington Consensus, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, working poor, working-age population, Works Progress Administration, yellow journalism, yield management

Big Data and Artificial Intelligence. The core of the optimists’ case lies not with physical robots or 3D printing but with the growing sophistication and humanlike abilities of computers that are often described as “artificial intelligence.” Brynjolfsson and McAfee provide many examples to demonstrate that computers are becoming sufficiently intelligent to supplant a growing share of human jobs. “They wonder if automation technology is near a tipping point, when machines finally master traits that have kept human workers irreplaceable.“56 Thus far, it appears that the vast majority of big data is being analyzed within large corporations for marketing purposes. The Economist reported recently that corporate IT expenditures for marketing purposes were increasing at three times the rate of other corporate IT expenditures.


pages: 540 words: 103,101

Building Microservices by Sam Newman

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airport security, Amazon Web Services, anti-pattern, business process, call centre, continuous integration, create, read, update, delete, defense in depth, don't repeat yourself, Edward Snowden, fault tolerance, index card, information retrieval, Infrastructure as a Service, inventory management, job automation, load shedding, loose coupling, platform as a service, premature optimization, pull request, recommendation engine, social graph, software as a service, source of truth, the built environment, web application, WebSocket, x509 certificate

This in turn helps the communication between the various business stakeholders and the team delivering features for them. Each squad inside a line of business is expected to own the entire lifecycle of the services it creates, including building, testing and releasing, supporting, and even decommissioning. A core delivery services team provides advice and guidance to these teams, as well as tooling to help it get the job done. A strong culture of automation is key, and REA makes heavy use of AWS as a key part of enabling the teams to be more autonomous. Figure 10-1 illustrates how this all works. Figure 10-1. An overview of Realestate.com.au’s organizational and team structure, and alignment with architecture It isn’t just the delivery organization that is aligned to how the business operates. It extends to the architecture too.


pages: 362 words: 99,063

The Education of Millionaires: It's Not What You Think and It's Not Too Late by Michael Ellsberg

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affirmative action, Black Swan, Burning Man, corporate governance, creative destruction, financial independence, follow your passion, future of work, hiring and firing, job automation, knowledge worker, Lean Startup, Mark Zuckerberg, means of production, mega-rich, meta analysis, meta-analysis, new economy, Norman Mailer, Peter Thiel, profit motive, race to the bottom, Sand Hill Road, shareholder value, side project, Silicon Valley, Skype, Steve Ballmer, survivorship bias, telemarketer, Tony Hsieh

He says that many young people, raised for years and years through the hoop-jumping and conformism of the formal schooling system, have an incredibly hard time answering it. So it weeds out most applicants: “Tell me something that you think is true that very few people agree with.” We’ve seen that those who have clung to outmoded, rigid, stale, conformist notions of formal higher education are now getting slaughtered economically, as their formerly safe jobs get outsourced, downsized, offshored, and automated, and as once-secure establishments crumble into the wireless, digital, networked ethers. What do you think is true about your own education, and about your own path to success in the real world, which very few people agree with? I hope this book has inspired at least a few disobedient thoughts. GRATITUDE This book would not exist without the encouragement of Marie Forleo.


pages: 315 words: 93,522

How Music Got Free: The End of an Industry, the Turn of the Century, and the Patient Zero of Piracy by Stephen Witt

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4chan, barriers to entry, Berlin Wall, big-box store, cloud computing, collaborative economy, crowdsourcing, game design, Internet Archive, invention of movable type, inventory management, iterative process, Jason Scott: textfiles.com, job automation, late fees, mental accounting, moral panic, packet switching, pattern recognition, peer-to-peer, pirate software, Ronald Reagan, security theater, sharing economy, side project, Silicon Valley, software patent, Steve Jobs, zero day

There was some kind of future here, maybe as a technician, maybe as an overseer. Reaching those heights required only dedication, and the lessons of Shoney’s applied. In fact, opportunities for advancement were everywhere. The Baptist backwoods of the Carolina foothills were transforming into America’s fastest-growing industrial corridor. In most of the country manufacturing jobs were vanishing, as work was automated or outsourced to Latin America and Asia. But in the Southeast United States the reverse was happening, as favorable tax rates, cheap land, and an antipathy toward organized labor attracted the attention of multinational corporations. In 1993, BMW had opened its first ever automobile factory outside of Germany: not in China, nor Mexico, but Spartanburg, South Carolina, just across the state line from Glover’s hometown.


pages: 525 words: 116,295

The New Digital Age: Transforming Nations, Businesses, and Our Lives by Eric Schmidt, Jared Cohen

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3D printing, access to a mobile phone, additive manufacturing, airport security, Amazon Mechanical Turk, Amazon Web Services, anti-communist, augmented reality, Ayatollah Khomeini, barriers to entry, bitcoin, borderless world, call centre, Chelsea Manning, citizen journalism, clean water, cloud computing, crowdsourcing, data acquisition, Dean Kamen, drone strike, Elon Musk, failed state, fear of failure, Filter Bubble, Google Earth, Google Glasses, hive mind, income inequality, information trail, invention of the printing press, job automation, John Markoff, Julian Assange, Khan Academy, Kickstarter, knowledge economy, Law of Accelerating Returns, market fundamentalism, means of production, mobile money, mutually assured destruction, Naomi Klein, offshore financial centre, Parag Khanna, peer-to-peer, peer-to-peer lending, personalized medicine, Peter Singer: altruism, Ray Kurzweil, RFID, Robert Bork, self-driving car, sentiment analysis, Silicon Valley, Skype, Snapchat, social graph, speech recognition, Steve Jobs, Steven Pinker, Stewart Brand, Stuxnet, The Wisdom of Crowds, upwardly mobile, Whole Earth Catalog, WikiLeaks, young professional, zero day

Perhaps a human-rights organization with staff living in a country under heavy diplomatic sanctions will pay its employees in mobile money credits, or in an entirely digital currency. As fewer jobs require a physical presence, talented individuals will have more options available to them. Skilled young adults in Uruguay will find themselves competing for certain types of jobs against their counterparts in Orange County. Of course, just as not all jobs can or will be automated in the future, not every job can be conducted from a distance—but more can than you might think. And for those living on a few dollars per day, there will be endless opportunities to increase their earnings. In fact, Amazon Mechanical Turk, which is a digital task-distribution platform, offers a present-day example of a company outsourcing small tasks that can be performed for a few cents by anyone with an Internet connection.


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Dark Money: The Hidden History of the Billionaires Behind the Rise of the Radical Right by Jane Mayer

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affirmative action, Affordable Care Act / Obamacare, American Legislative Exchange Council, anti-communist, Bakken shale, bank run, battle of ideas, Berlin Wall, Capital in the Twenty-First Century by Thomas Piketty, carried interest, centre right, clean water, Climategate, Climatic Research Unit, collective bargaining, corporate raider, crony capitalism, David Brooks, desegregation, diversified portfolio, Donald Trump, energy security, estate planning, Fall of the Berlin Wall, George Gilder, housing crisis, hydraulic fracturing, income inequality, Intergovernmental Panel on Climate Change (IPCC), invisible hand, job automation, low skilled workers, mandatory minimum, market fundamentalism, mass incarceration, Mont Pelerin Society, More Guns, Less Crime, Nate Silver, New Journalism, obamacare, Occupy movement, offshore financial centre, oil shale / tar sands, oil shock, Plutocrats, plutocrats, Powell Memorandum, Ralph Nader, Renaissance Technologies, road to serfdom, Ronald Reagan, school choice, school vouchers, The Bell Curve by Richard Herrnstein and Charles Murray, The Chicago School, the scientific method, University of East Anglia, Unsafe at Any Speed, War on Poverty, working poor

Their heirs, however, with the help of the Milwaukee law firm Foley & Lardner, managed to sell the company to Rockwell nonetheless, cashing in handsomely. One of the law firm’s partners, Michael Grebe, subsequently became chairman and CEO of the newly enriched foundation. What remained of Allen-Bradley, however, did less well. Its sad slide traced the fall of American manufacturing during the end of the twentieth century and the hollowing out of decent blue-collar jobs. In 2010, Rockwell Automation, which is what was left of the company in Milwaukee twenty-five years after it was sold, outsourced the last of the plant’s remaining manufacturing jobs to low-wage areas, largely in Latin America and Asia. Robert Granum, president of Local 1111 of the United Electrical, Radio, and Machine Workers of America, the union that represented the last laid-off workers, told the Milwaukee Business Journal that Rockwell’s decision would “deprive future generations of working people of the opportunity to have decent family-supporting jobs.”


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Exceptional People: How Migration Shaped Our World and Will Define Our Future by Ian Goldin, Geoffrey Cameron, Meera Balarajan

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Admiral Zheng, agricultural Revolution, barriers to entry, Berlin Wall, Branko Milanovic, British Empire, conceptual framework, creative destruction, demographic transition, Deng Xiaoping, endogenous growth, failed state, Fall of the Berlin Wall, Gini coefficient, global supply chain, guest worker program, illegal immigration, income inequality, income per capita, Intergovernmental Panel on Climate Change (IPCC), job automation, Joseph Schumpeter, knowledge economy, labor-force participation, labour mobility, Lao Tzu, life extension, low skilled workers, low-wage service sector, Malacca Straits, mass immigration, microcredit, Network effects, new economy, New Urbanism, old age dependency ratio, open borders, out of africa, price mechanism, purchasing power parity, Richard Florida, selection bias, Silicon Valley, Silicon Valley startup, Skype, spice trade, trade route, transaction costs, transatlantic slave trade, transatlantic slave trade, women in the workforce, working-age population

Absolute changes in labor demand will depend on the extent to which new technologies substitute for workers, but low-skilled work in the service sector and high-skilled work in knowledge-based sectors will resist such change. The fastest growing areas of employment—in health care and IT, for example—already draw disproportionately on migrant labor. Technological change creates new types of jobs for high-skilled workers, and there are limits to the low-skilled jobs it can replace. Machines and automation may reduce the labor inputs at a manufacturing plant, but they cannot staff a pharmacy, provide child care, or attend to an elderly patient. Industries that are particularly starved for labor will lobby for opening borders to low-skilled and high-skilled migrants alike. While the decision to expand immigration quotas is a political one, history shows that migration often occurs in spite of official policy and not always because of it.


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The Black Box Society: The Secret Algorithms That Control Money and Information by Frank Pasquale

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Affordable Care Act / Obamacare, algorithmic trading, Amazon Mechanical Turk, American Legislative Exchange Council, asset-backed security, Atul Gawande, bank run, barriers to entry, basic income, Berlin Wall, Bernie Madoff, Black Swan, bonus culture, Brian Krebs, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chelsea Manning, Chuck Templeton: OpenTable, cloud computing, collateralized debt obligation, computerized markets, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, Debian, don't be evil, drone strike, Edward Snowden, en.wikipedia.org, Fall of the Berlin Wall, Filter Bubble, financial innovation, financial thriller, fixed income, Flash crash, full employment, Goldman Sachs: Vampire Squid, Google Earth, Hernando de Soto, High speed trading, hiring and firing, housing crisis, informal economy, information asymmetry, information retrieval, interest rate swap, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, Julian Assange, Kevin Kelly, knowledge worker, Kodak vs Instagram, kremlinology, late fees, London Interbank Offered Rate, London Whale, Marc Andreessen, Mark Zuckerberg, mobile money, moral hazard, new economy, Nicholas Carr, offshore financial centre, PageRank, pattern recognition, Philip Mirowski, precariat, profit maximization, profit motive, quantitative easing, race to the bottom, recommendation engine, regulatory arbitrage, risk-adjusted returns, Satyajit Das, search engine result page, shareholder value, Silicon Valley, Snapchat, Spread Networks laid a new fibre optics cable between New York and Chicago, statistical arbitrage, statistical model, Steven Levy, the scientific method, too big to fail, transaction costs, two-sided market, universal basic income, Upton Sinclair, value at risk, WikiLeaks, zero-sum game

Similar software analyzes callers simultaneously, matching them to agents via emotion-parsing algorithms. Sound furious as you talk your way through a phone tree, and you may be routed to someone with anger management training. Or not; some companies work extra hard to soothe, but others just dump problem customers. There’s a fi ne line between the wooed and the waste. “Data-driven” management promises a hyperefficient workplace. The most watched jobs are also the easiest to automate: a comprehensive documentation of everything a worker has done is the key data enabling a robot to take her place.93 But good luck finding out exactly how management protocols work. If they were revealed, the bosses claim, employees would game the system. If workers knew that thirty-three-word e-mails littered with emoticons scored highest, they might write that way all the time.


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The American Way of Poverty: How the Other Half Still Lives by Sasha Abramsky

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, Affordable Care Act / Obamacare, American Legislative Exchange Council, bank run, basic income, big-box store, collective bargaining, deindustrialization, fixed income, Francis Fukuyama: the end of history, full employment, ghettoisation, Gini coefficient, housing crisis, illegal immigration, immigration reform, income inequality, indoor plumbing, job automation, Mark Zuckerberg, Maui Hawaii, microcredit, mortgage debt, mortgage tax deduction, new economy, Occupy movement, offshore financial centre, payday loans, Plutocrats, plutocrats, Ponzi scheme, Potemkin village, profit motive, Ronald Reagan, school vouchers, upwardly mobile, War on Poverty, Washington Consensus, women in the workforce, working poor, working-age population, Works Progress Administration

.; Newark; Detroit; Chicago; Los Angeles; New Orleans; and many other cities were equally apocalyptic. In Detroit, for example, where hundreds of thousands of workers had once made good money working in auto manufacturing, so many people had departed the city in recent decades, and so many lots had been abandoned, that in large numbers of neighborhoods there were more vacant homes than occupied ones. From the 1960s onward, plants started to shed jobs, as production processes increasingly became automated. In 1979, for example, General Motors was producing as many cars in Detroit as it had done twenty years earlier, but with half the number of workers. Finally, however, even those workers proved too costly, and companies shuttered their factories entirely, the jobs outsourced to nonunion sites in other states, or overseas. Once iconic factories, such as the enormous Packard complex that, at its mighty zenith, had employed 60,000 people, remained only as vast shells, the ground carpeted by broken glass, the entranceways to buildings that used to house state-of-the-art industrial machinery piled high with tires, bricks, and twisted metal piping.


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Homo Deus: A Brief History of Tomorrow by Yuval Noah Harari

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23andMe, agricultural Revolution, algorithmic trading, Anne Wojcicki, anti-communist, Anton Chekhov, autonomous vehicles, Berlin Wall, call centre, Chris Urmson, cognitive dissonance, Columbian Exchange, computer age, Deng Xiaoping, don't be evil, drone strike, European colonialism, experimental subject, falling living standards, Flash crash, Frank Levy and Richard Murnane: The New Division of Labor, glass ceiling, global village, Intergovernmental Panel on Climate Change (IPCC), invention of writing, invisible hand, Isaac Newton, job automation, John Markoff, Kevin Kelly, lifelogging, means of production, Mikhail Gorbachev, Minecraft, Moneyball by Michael Lewis explains big data, mutually assured destruction, new economy, pattern recognition, Peter Thiel, placebo effect, Ray Kurzweil, self-driving car, Silicon Valley, Silicon Valley ideology, stem cell, Steven Pinker, telemarketer, The Future of Employment, too big to fail, trade route, Turing machine, Turing test, ultimatum game, Watson beat the top human players on Jeopardy!, zero-sum game

Soon enough, many other baseball teams adopted the same algorithmic approach, and since the Yankees and Red Sox could pay far more for both baseball players and computer software, low-budget teams such as the Oakland Athletics now had an even smaller chance of beating the system than before.14 In 2004 Professor Frank Levy from MIT and Professor Richard Murnane from Harvard published a thorough research of the job market, listing those professions most likely to undergo automation. Truck drivers were given as an example of a job that could not possibly be automated in the foreseeable future. It is hard to imagine, they wrote, that algorithms could safely drive trucks on a busy road. A mere ten years later, Google and Tesla not only imagine this, but are actually making it happen.15 In fact, as time goes by, it becomes easier and easier to replace humans with computer algorithms, not merely because the algorithms are getting smarter, but also because humans are professionalising.


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In Our Own Image: Savior or Destroyer? The History and Future of Artificial Intelligence by George Zarkadakis

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3D printing, Ada Lovelace, agricultural Revolution, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, anthropic principle, Asperger Syndrome, autonomous vehicles, barriers to entry, battle of ideas, Berlin Wall, bioinformatics, British Empire, business process, carbon-based life, cellular automata, Claude Shannon: information theory, combinatorial explosion, complexity theory, continuous integration, Conway's Game of Life, cosmological principle, dark matter, dematerialisation, double helix, Douglas Hofstadter, Edward Snowden, epigenetics, Flash crash, Google Glasses, Gödel, Escher, Bach, income inequality, index card, industrial robot, Internet of things, invention of agriculture, invention of the steam engine, invisible hand, Isaac Newton, Jacquard loom, Jacquard loom, Jacques de Vaucanson, James Watt: steam engine, job automation, John von Neumann, Joseph-Marie Jacquard, liberal capitalism, lifelogging, millennium bug, Moravec's paradox, natural language processing, Norbert Wiener, off grid, On the Economy of Machinery and Manufactures, packet switching, pattern recognition, Paul Erdős, post-industrial society, prediction markets, Ray Kurzweil, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, speech recognition, stem cell, Stephen Hawking, Steven Pinker, strong AI, technological singularity, The Coming Technological Singularity, The Future of Employment, the scientific method, theory of mind, Turing complete, Turing machine, Turing test, Tyler Cowen: Great Stagnation, Vernor Vinge, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Y2K


The Singularity Is Near: When Humans Transcend Biology by Ray Kurzweil

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additive manufacturing, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anthropic principle, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, Benoit Mandelbrot, Bill Joy: nanobots, bioinformatics, brain emulation, Brewster Kahle, Brownian motion, business intelligence, c2.com, call centre, carbon-based life, cellular automata, Claude Shannon: information theory, complexity theory, conceptual framework, Conway's Game of Life, cosmological constant, cosmological principle, cuban missile crisis, data acquisition, Dava Sobel, David Brooks, Dean Kamen, disintermediation, double helix, Douglas Hofstadter, en.wikipedia.org, epigenetics, factory automation, friendly AI, George Gilder, Gödel, Escher, Bach, informal economy, information retrieval, invention of the telephone, invention of the telescope, invention of writing, Isaac Newton, iterative process, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, John von Neumann, Kevin Kelly, Law of Accelerating Returns, life extension, lifelogging, linked data, Loebner Prize, Louis Pasteur, mandelbrot fractal, Mikhail Gorbachev, mouse model, Murray Gell-Mann, mutually assured destruction, natural language processing, Network effects, new economy, Norbert Wiener, oil shale / tar sands, optical character recognition, pattern recognition, phenotype, premature optimization, randomized controlled trial, Ray Kurzweil, remote working, reversible computing, Richard Feynman, Richard Feynman, Robert Metcalfe, Rodney Brooks, Search for Extraterrestrial Intelligence, selection bias, semantic web, Silicon Valley, Singularitarianism, speech recognition, statistical model, stem cell, Stephen Hawking, Stewart Brand, strong AI, superintelligent machines, technological singularity, Ted Kaczynski, telepresence, The Coming Technological Singularity, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Y2K, Yogi Berra