Demis Hassabis

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Genius Makers: The Mavericks Who Brought A. I. To Google, Facebook, and the World by Cade Metz

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built a system that could read passages from The Lord of the Rings: Metz, “Facebook Aims Its AI at the Game No Computer Can Crack.” Demis Hassabis appeared in an online video: “Interview with Demis Hassabis,” YouTube, https://www.youtube.com/watch?v=EhAjLnT9aL4. “I can’t talk about it yet”: Ibid. Hassabis and DeepMind revealed that their AI system, AlphaGo: Cade Metz, “In a Huge Breakthrough, Google’s AI Beats a Top Player at the Game of Go,” Wired, January 27, 2016, https://www.wired.com/2016/01/in-a-huge-breakthrough-googles-ai-beats-a-top-player-at-the-game-of-go/. Demis Hassabis and several other DeepMind researchers: Cade Metz, “What the AI Behind AlphaGo Can Teach Us About Being Human,” Wired, May 19, 2016, https://www.wired.com/2016/05/google-alpha-go-ai/.

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ERIC SCHMIDT, chairman. AT DEEPMIND ALEX GRAVES, the Scottish researcher who built a system that could write in longhand. DEMIS HASSABIS, the British chess prodigy, game designer, and neuroscientist who founded DeepMind, a London AI start-up that would grow into the world’s most celebrated AI lab. KORAY KAVUKCUOGLU, the Turkish researcher who oversaw the lab’s software code. SHANE LEGG, the New Zealander who founded DeepMind alongside Demis Hassabis, intent on building machines that could do anything the brain could do—even as he worried about the dangers this could bring. VLAD MNIH, the Russian researcher who oversaw the creation of a machine that mastered old Atari games.

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As the lawyer saw it, he had two options: He could hire a professional negotiator and risk angering the companies he hoped would acquire his tiny venture, or he could set up an auction. Hinton chose an auction. In the end, four names joined the bidding for his new company: Baidu, Google, Microsoft, and a two-year-old start-up most of the world had never heard of. This was DeepMind, a London company founded by a young neuroscientist named Demis Hassabis that would grow to become the most celebrated and influential AI lab of the decade. The week of the auction, Alan Eustace, Google’s head of engineering, flew his own twin-engine plane into the airport near the south shore of Lake Tahoe. He and Jeff Dean, Google’s most revered engineer, had dinner with Hinton and his students in the restaurant on the top floor of Harrah’s, a steak house decorated with a thousand empty wine bottles.

Architects of Intelligence by Martin Ford

3D printing, agricultural Revolution, AI winter, algorithmic bias, Alignment Problem, AlphaGo, Apple II, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, backpropagation, barriers to entry, basic income, Baxter: Rethink Robotics, Bayesian statistics, Big Tech, bitcoin, Boeing 747, Boston Dynamics, business intelligence, business process, call centre, Cambridge Analytica, cloud computing, cognitive bias, Colonization of Mars, computer vision, Computing Machinery and Intelligence, correlation does not imply causation, CRISPR, crowdsourcing, DARPA: Urban Challenge, data science, deep learning, DeepMind, Demis Hassabis, deskilling, disruptive innovation, Donald Trump, Douglas Hofstadter, driverless car, Elon Musk, Erik Brynjolfsson, Ernest Rutherford, fake news, Fellow of the Royal Society, Flash crash, future of work, general purpose technology, Geoffrey Hinton, gig economy, Google X / Alphabet X, Gödel, Escher, Bach, Hans Moravec, Hans Rosling, hype cycle, ImageNet competition, income inequality, industrial research laboratory, industrial robot, information retrieval, job automation, John von Neumann, Large Hadron Collider, Law of Accelerating Returns, life extension, Loebner Prize, machine translation, Mark Zuckerberg, Mars Rover, means of production, Mitch Kapor, Mustafa Suleyman, natural language processing, new economy, Nick Bostrom, OpenAI, opioid epidemic / opioid crisis, optical character recognition, paperclip maximiser, pattern recognition, phenotype, Productivity paradox, radical life extension, Ray Kurzweil, recommendation engine, Robert Gordon, Rodney Brooks, Sam Altman, self-driving car, seminal paper, sensor fusion, sentiment analysis, Silicon Valley, smart cities, social intelligence, sparse data, speech recognition, statistical model, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, synthetic biology, systems thinking, Ted Kaczynski, TED Talk, The Rise and Fall of American Growth, theory of mind, Thomas Bayes, Travis Kalanick, Turing test, universal basic income, Wall-E, Watson beat the top human players on Jeopardy!, women in the workforce, working-age population, workplace surveillance , zero-sum game, Zipcar

She is the co-founder of AI4ALL, an organization focused on attracting women and people from underrepresented groups into the field of AI, which began at Stanford and has now scaled up to universities across the United States. Chapter 8. DEMIS HASSABIS Games are just our training domain. We’re not doing all this work just to solve games; we want to build these general algorithms that we can apply to real-world problems. CO-FOUNDER & CEO OF DEEPMIND AI RESEARCHER AND NEUROSCIENTIST Demis Hassabis is a former child chess prodigy, who started coding and designing video games professionally at age 16. After graduating from Cambridge University, Demis spent a decade leading and founding successful startups focused on video games and simulation.

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They agreed to give us autonomy as to our research roadmap and our culture, and also to staying in London, which was very important to me. Finally, they also agreed to have an ethics board concerning our technology, which was very unusual but very prescient of them. MARTIN FORD: Why did you choose to be in London, and not Silicon Valley? Is that a Demis Hassabis or a DeepMind thing? DEMIS HASSABIS: Both really. I’m a born-and-bred Londoner, and I love London, but at the same time, I thought it was a competitive advantage because the UK and Europe have amazing universities in the field of AI like Cambridge and Oxford. But also, at the time there was no real ambitious research company in the UK, or really in Europe, so our hiring prospects were high, especially with all these universities outputting great postgraduate and graduate students.

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Ultimately, this is going to be of global significance and having different voices about how to use it, what to use it for, and how to distribute the proceeds, is important. MARTIN FORD: I believe you’re also opening up labs in other European cities? DEMIS HASSABIS: We’ve opened a small research lab in Paris, which is our first continental European office. We’ve also opened two labs in Canada in Alberta and Montreal. More recently, since joining Google, we now have an applied team office in Mountain View, California who are right next to the Google teams that we work with. MARTIN FORD: How closely do you work with the other AI teams at Google? DEMIS HASSABIS: Google’s a huge place, and there are thousands of people working on every aspect of machine learning and AI, from both a very applied perspective to a pure research point of view.

Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell

Ada Lovelace, AI winter, Alignment Problem, AlphaGo, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, artificial general intelligence, autonomous vehicles, backpropagation, Bernie Sanders, Big Tech, Boston Dynamics, Cambridge Analytica, Charles Babbage, Claude Shannon: information theory, cognitive dissonance, computer age, computer vision, Computing Machinery and Intelligence, dark matter, deep learning, DeepMind, Demis Hassabis, Douglas Hofstadter, driverless car, Elon Musk, en.wikipedia.org, folksonomy, Geoffrey Hinton, Gödel, Escher, Bach, I think there is a world market for maybe five computers, ImageNet competition, Jaron Lanier, job automation, John Markoff, John von Neumann, Kevin Kelly, Kickstarter, license plate recognition, machine translation, Mark Zuckerberg, natural language processing, Nick Bostrom, Norbert Wiener, ought to be enough for anybody, paperclip maximiser, pattern recognition, performance metric, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rodney Brooks, self-driving car, sentiment analysis, Silicon Valley, Singularitarianism, Skype, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, tacit knowledge, tail risk, TED Talk, the long tail, theory of mind, There's no reason for any individual to have a computer in his home - Ken Olsen, trolley problem, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, world market for maybe five computers

Johns, “Transferring End-to-End Visuomotor Control from Simulation to Real World for a Multi-stage Task,” in Proceedings of the First Annual Conference on Robot Learning, CoRL (2017); M. Cutler, T. J. Walsh, and J. P. How, “Real-World Reinforcement Learning via Multifidelity Simulators,” IEEE Transactions on Robotics 31, no. 3 (2015): 655–71. 9: Game On   1.  Demis Hassabis, quoted in P. Iwaniuk, “A Conversation with Demis Hassabis, the Bullfrog AI Prodigy Now Finding Solutions to the World’s Big Problems,” PCGamesN, accessed Dec. 7, 2018, www.pcgamesn.com/demis-hassabis-interview.   2.  Quoted in “From Not Working to Neural Networking,” Economist, June 25, 2016.   3.  M. G. Bellemare et al., “The Arcade Learning Environment: An Evaluation Platform for General Agents,” Journal of Artificial Intelligence Research 47 (2013): 253–79.   4.  

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Taylor, “The Concept of ‘Cat Face,’” London Review of Books, Aug. 11, 2016. 26.  Quoted in S. Byford, “DeepMind Founder Demis Hassabis on How AI Will Shape the Future,” Verge, March 10, 2016, www.theverge.com/2016/3/10/11192774/demis-hassabis-interview-alphago-google-deepmind-ai. 27.  D. Silver et al., “Mastering the Game of Go Without Human Knowledge,” Nature, 550 (2017): 354–59. 28.  D. Silver et al., “A General Reinforcement Learning Algorithm That Masters Chess, Shogi, and Go Through Self-Play,” Science 362, no. 6419 (2018): 1140–44. 10: Beyond Games   1.  Quoted in P. Iwaniuk, “A Conversation with Demis Hassabis, the Bullfrog AI Prodigy Now Finding Solutions to the World’s Big Problems,” PCGamesN, accessed Dec. 7, 2018, www.pcgamesn.com/demis-hassabis-interview.   2.  

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Often it takes a kind of cabalistic knowledge that students of machine learning gain both from their apprenticeships with experts and from hard-won experience. As Eric Horvitz, director of Microsoft’s research lab, characterized it, “Right now, what we are doing is not a science but a kind of alchemy.”5 And the people who can do this kind of “network whispering” form a small, exclusive club: according to Demis Hassabis, cofounder of Google DeepMind, “It’s almost like an art form to get the best out of these systems.… There’s only a few hundred people in the world that can do that really well.”6 Actually, the number of deep-learning experts is growing quickly; many universities now offer courses in the subject, and a growing list of companies have started their own deep-learning training programs for employees.

Rule of the Robots: How Artificial Intelligence Will Transform Everything by Martin Ford

AI winter, Airbnb, algorithmic bias, algorithmic trading, Alignment Problem, AlphaGo, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, Automated Insights, autonomous vehicles, backpropagation, basic income, Big Tech, big-box store, call centre, carbon footprint, Chris Urmson, Claude Shannon: information theory, clean water, cloud computing, commoditize, computer age, computer vision, Computing Machinery and Intelligence, coronavirus, correlation does not imply causation, COVID-19, crowdsourcing, data is the new oil, data science, deep learning, deepfake, DeepMind, Demis Hassabis, deskilling, disruptive innovation, Donald Trump, Elon Musk, factory automation, fake news, fulfillment center, full employment, future of work, general purpose technology, Geoffrey Hinton, George Floyd, gig economy, Gini coefficient, global pandemic, Googley, GPT-3, high-speed rail, hype cycle, ImageNet competition, income inequality, independent contractor, industrial robot, informal economy, information retrieval, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jeff Bezos, job automation, John Markoff, Kiva Systems, knowledge worker, labor-force participation, Law of Accelerating Returns, license plate recognition, low interest rates, low-wage service sector, Lyft, machine readable, machine translation, Mark Zuckerberg, Mitch Kapor, natural language processing, Nick Bostrom, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, Ocado, OpenAI, opioid epidemic / opioid crisis, passive income, pattern recognition, Peter Thiel, Phillips curve, post scarcity, public intellectual, Ray Kurzweil, recommendation engine, remote working, RFID, ride hailing / ride sharing, Robert Gordon, Rodney Brooks, Rubik’s Cube, Sam Altman, self-driving car, Silicon Valley, Silicon Valley startup, social distancing, SoftBank, South of Market, San Francisco, special economic zone, speech recognition, stealth mode startup, Stephen Hawking, superintelligent machines, TED Talk, The Future of Employment, The Rise and Fall of American Growth, the scientific method, Turing machine, Turing test, Tyler Cowen, Tyler Cowen: Great Stagnation, Uber and Lyft, uber lyft, universal basic income, very high income, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y Combinator

Filip Piekniewski, “AI winter is well on its way,” Piekniewski’s Blog, May 28, 2018, blog.piekniewski.info/2018/05/28/ai-winter-is-well-on-its-way/. 16. Ford, Interview with Jeffery Dean, in Architects of Intelligence, p. 377. 17. Ford, Interview with Demis Hassabis, in Architects of Intelligence, p. 171. 18. Andrea Banino, Caswell Barry, Dharshan Kumaran and Benigno Uria, “Navigating with grid-like representations in artificial agents,” DeepMind Research Blog, May 9, 2018, deepmind.com/blog/article/grid-cells. 19. Ford, Interview with Demis Hassabis, in Architects of Intelligence, p. 173. 20. Andrea Banino, Caswell Barry, Benigno Uria et al., “Vector-based navigation using grid-like representations in artificial agents,” Nature, volume 557, pp. 429–433 (2018), May 9, 2018, www.nature.com/articles/s41586-018-0102-6. 21.

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According to one theory, Go was invented during the reign of the emperor Yao, sometime prior to 2000 BC.6 The ability to play Go, along with expertise in calligraphy, painting and playing a stringed musical instrument, was viewed as one of the four primary arts that marked ancient Chinese scholarship. Unlike chess, the game of Go is so complex as to be immune to the onslaught of brute force algorithms. During the course of the game, the board, which consists of a nineteen-by-nineteen grid, is largely filled with black and white game pieces called “stones.” As DeepMind CEO Demis Hassabis often likes to point out when he discusses AlphaGo’s accomplishment, the number of possible arrangements of the stones on the board exceeds the estimated number of atoms in the known universe. Over the thousands of years that the game has been played, it is extraordinarily—indeed vanishingly—unlikely that any two games have unfolded in identical fashion.

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What they all have in common is that their ultimate objectives are modeled on capabilities that, at least so far, are exclusive to human cognition. One important approach is to look directly to the inner workings of the human brain for inspiration. These researchers believe that artificial intelligence should be directly informed by neuroscience. The leader in this area is DeepMind. The company’s founder and CEO, Demis Hassabis—unusually for an AI researcher—received his graduate training in neuroscience, rather than computing, and holds a PhD in the field from University College, London. Hassabis told me that the single largest research group at DeepMind consists of neuroscientists who are focused on finding ways to apply the latest insights from brain science to artificial intelligence.17 Their objective is not to replicate the way the brain works in any detailed sense, but rather to be inspired by the basic principles that underlie its operation.

Spike: The Virus vs The People - The Inside Story by Jeremy Farrar, Anjana Ahuja

"World Economic Forum" Davos, bioinformatics, Black Monday: stock market crash in 1987, Boris Johnson, Brexit referendum, contact tracing, coronavirus, COVID-19, crowdsourcing, dark matter, data science, DeepMind, Demis Hassabis, disinformation, Dominic Cummings, Donald Trump, double helix, dual-use technology, Future Shock, game design, global pandemic, Kickstarter, lab leak, lockdown, machine translation, nudge unit, open economy, pattern recognition, precautionary principle, side project, social distancing, the scientific method, Tim Cook: Apple, zoonotic diseases

Adding in the chief scientists and other emissaries for various government departments, plus the devolved nations, I would guess that SAGE has between 200 and 300 people to call on in total, although there were rarely more than 20 to 30 in attendance (plus others dialling in on often ropey lines). I do not recall Treasury officials at the meetings I attended. Outsiders were occasionally invited in; at one meeting I sat next to Demis Hassabis, a researcher who cofounded artificial intelligence start-up DeepMind. The SAGE meetings mostly took place in a basement at 10 Victoria Street in Westminster, which also houses the Government Office for Science. We would go through security and head downstairs through corridors with peeling paint.

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We should try to lock everything down as fast as we possibly can.”’ That was my view, and I am sure most people on SAGE agreed. Cummings was also courting the views of three scientists beyond SAGE, to whom he was occasionally sending SAGE papers: Venki Ramakrishnan, president of the Royal Society and a chemistry Nobel laureate; Demis Hassabis; and Timothy Gowers, the British mathematician and Fields medallist. I saw both Demis and Venki at the odd SAGE meeting but not Timothy. Timothy told Cummings in a series of emails that, in his view, the best strategy was to go in hard and early on interventions like lockdowns, because of exponential growth in case numbers.

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It was a constructive intervention. So, by 16 March, the judgement from outbreak veterans, epidemiological modellers and the UK’s behavioural science community had reached a consensus: act now. SAGE met again on Wednesday 18 March, a day on which 999 fresh coronavirus cases were reported across the UK. I sat between Demis Hassabis and Ian Diamond, the brilliant chief statistician at the Office for National Statistics. There were around a dozen advisers in the room, and as many others dialling in, plus a handful of SAGE administrative staff. We were facing a terrible situation: the UK was estimated to be between two and four weeks behind Italy on its epidemic curve.

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

3D printing, Ada Lovelace, AI winter, Airbnb, Alvin Toffler, artificial general intelligence, augmented reality, barriers to entry, basic income, bitcoin, Bletchley Park, blockchain, brain emulation, Buckminster Fuller, Charles Babbage, cloud computing, computer age, computer vision, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, deep learning, DeepMind, dematerialisation, Demis Hassabis, discovery of the americas, disintermediation, don't be evil, driverless car, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, everywhere but in the productivity statistics, Flash crash, friendly AI, Geoffrey Hinton, Google Glasses, hedonic treadmill, hype cycle, 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, machine translation, Mahatma Gandhi, means of production, mutually assured destruction, Neil Armstrong, Nicholas Carr, Nick Bostrom, paperclip maximiser, pattern recognition, peer-to-peer, peer-to-peer model, Peter Thiel, radical life extension, Ray Kurzweil, Robert Solow, 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, TED Talk, The future is already here, The Future of Employment, theory of mind, Turing machine, Turing test, universal basic income, Vernor Vinge, wage slave, Wall-E, zero-sum game

The system’s first attempt at each game was disastrous but by playing continuously for 24 hours or so it worked out – through trial and error – the subtleties in the gameplay and scoring system, and played the game better than the best human player. It took longer to master Space Invaders, where the winning strategies are less obvious. DeepMind’s founder, Demis Hassabis, remarked that it is easier to experiment with AI using video games than robots because it avoids the messy business of hydraulics, power and gravity that dealing with the real world entails. But the hand-eye co-ordination could well prove useful with real-world robots as well as video games.

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Will you be reminded to take your pill in the morning because its bottle starts glowing, or will Hermione alert you? No doubt the outcome will seem obvious in hindsight. It has been said that all industries are now part of the information industry – or heading that way. Much of the cost of developing a modern car – and much of the quality of its performance – lies in the software that controls it. Demis Hassabis has said that AI converts information into knowledge, which he sees as empowering people. The mission statement of Google, the new owner of his company, is to organise the world’s information and make it universally accessible and useful. For many of us, most of the tasks that we perform each day can be broken down into four fundamental skills: looking, reading, writing, and integrating knowledge.

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Unless you have direct exposure to groups like Deepmind, you have no idea how fast – it is growing at a pace close to exponential. The risk of something seriously dangerous happening is in the five year timeframe. 10 years at most. This is not a case of crying wolf about something I don’t understand.” Demis Hassabis, founder of the company Musk was referring to responded by downplaying the immediacy of the threat: “We agree with him there are risks that need to be borne in mind, but we’re decades away from any sort of technology that we need to worry about,” Whatever you think of Musk’s warnings, he has at least put his money where his mouth is.

The Deep Learning Revolution (The MIT Press) by Terrence J. Sejnowski

AI winter, Albert Einstein, algorithmic bias, algorithmic trading, AlphaGo, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, autonomous vehicles, backpropagation, Baxter: Rethink Robotics, behavioural economics, bioinformatics, cellular automata, Claude Shannon: information theory, cloud computing, complexity theory, computer vision, conceptual framework, constrained optimization, Conway's Game of Life, correlation does not imply causation, crowdsourcing, Danny Hillis, data science, deep learning, DeepMind, delayed gratification, Demis Hassabis, Dennis Ritchie, discovery of DNA, Donald Trump, Douglas Engelbart, driverless car, Drosophila, Elon Musk, en.wikipedia.org, epigenetics, Flynn Effect, Frank Gehry, future of work, Geoffrey Hinton, Google Glasses, Google X / Alphabet X, Guggenheim Bilbao, Gödel, Escher, Bach, haute couture, Henri Poincaré, I think there is a world market for maybe five computers, industrial robot, informal economy, Internet of things, Isaac Newton, Jim Simons, John Conway, John Markoff, John von Neumann, language acquisition, Large Hadron Collider, machine readable, Mark Zuckerberg, Minecraft, natural language processing, Neil Armstrong, Netflix Prize, Norbert Wiener, OpenAI, orbital mechanics / astrodynamics, PageRank, pattern recognition, pneumatic tube, prediction markets, randomized controlled trial, Recombinant DNA, recommendation engine, Renaissance Technologies, Rodney Brooks, self-driving car, Silicon Valley, Silicon Valley startup, Socratic dialogue, speech recognition, statistical model, Stephen Hawking, Stuart Kauffman, theory of mind, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, Turing machine, Von Neumann architecture, Watson beat the top human players on Jeopardy!, world market for maybe five computers, X Prize, Yogi Berra

Indeed, stage actors know that if they don’t have butterflies in their stomachs before their performances, they won’t be Figure 1.9 Lee Sedol after losing the Go Challenge Match in March 2016. The Rise of Machine Learning 19 Figure 1.10 Demis Hassabis (left) and Ke Jie meet after the historic Go match in China in 2017, holding a board with Ke Jie’s signature. Courtesy of Demis Hassabis. in good form. Their performances follow an inverted U-shaped curve, with their best ones in an optimal state between low and high levels of arousal. Athletes call this being “in the zone.” AlphaGo also defeated a team of five top players on May 26, 2017.

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In one game, AlphaZero made a bold bishop sacrifice, sometimes used to gain positional advantage, followed by a queen sacrifice, which seemed like a colossal blunder until it led to a checkmate many moves later that neither Stockfish nor humans saw coming. The aliens have landed and the earth will never be the same again. AlphaGo’s developer, DeepMind, was cofounded in 2010 by neuroscientist Demis Hassabis (figure 1.10, left), who had been a postdoctoral fellow at University College London’s Gatsby Computational Neuroscience Unit (directed by Peter Dayan, a former postdoctoral fellow in my lab and winner of the prestigious Brain Prize in 2017 along with Raymond Dolan and Wolfram Schultz for their research on reward learning).

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There must be mechanisms based on local patterns of activity in the dendrites, somas and axons of neurons that dynamically regulate the locations and densities of these channels. Several algorithms have been suggested for how this could be accomplished.24 This form of homeostasis is not as well understood as homeostatic synaptic plasticity. What Is Missing? Demis Hassabis and I participated in intense debates about the future of and next priority for artificial intelligence that took place during the Brains, Minds and Machines symposium at the 2015 NIPS Conference in Montreal and the Bits and Brains workshop at the NIPS 2016 Conference in Barcelona. There are still many open questions in AI that need to be addressed.

On the Future: Prospects for Humanity by Martin J. Rees

23andMe, 3D printing, air freight, Alfred Russel Wallace, AlphaGo, Anthropocene, Asilomar, autonomous vehicles, Benoit Mandelbrot, biodiversity loss, blockchain, Boston Dynamics, carbon tax, circular economy, CRISPR, cryptocurrency, cuban missile crisis, dark matter, decarbonisation, DeepMind, Demis Hassabis, demographic transition, Dennis Tito, distributed ledger, double helix, driverless car, effective altruism, Elon Musk, en.wikipedia.org, Geoffrey Hinton, global village, Great Leap Forward, Higgs boson, Hyperloop, Intergovernmental Panel on Climate Change (IPCC), Internet of things, James Webb Space Telescope, Jeff Bezos, job automation, Johannes Kepler, John Conway, Large Hadron Collider, life extension, mandelbrot fractal, mass immigration, megacity, Neil Armstrong, Nick Bostrom, nuclear winter, ocean acidification, off-the-grid, pattern recognition, precautionary principle, quantitative hedge fund, Ray Kurzweil, Recombinant DNA, Rodney Brooks, Search for Extraterrestrial Intelligence, sharing economy, Silicon Valley, smart grid, speech recognition, Stanford marshmallow experiment, Stanislav Petrov, stem cell, Stephen Hawking, Steven Pinker, Stuxnet, supervolcano, technological singularity, the scientific method, Tunguska event, uranium enrichment, Walter Mischel, William MacAskill, Yogi Berra

I’m therefore grateful for the feedback from listeners and readers. And I acknowledge with special gratitude the input (knowing or unknowing) from friends and colleagues with specialised expertise, who are not specifically quoted in the text. Among them are (alphabetically) Partha Dasgupta, Stu Feldman, Ian Golden, Demis Hassabis, Hugh Hunt, Charlie Kennel, David King, Seán Ó hÉigeartaigh, Catharine Rhodes, Richard Roberts, Eric Schmidt, and Julius Weitzdorfer. I am specially grateful to Ingrid Gnerlich of Princeton University Press for instigating the book, and for her advice while I was writing it. I’m also grateful to Dawn Hall for the copyediting, to Julie Shawvan for the index, to Chris Ferrante for the text design, and to Jill Harris, Sara Henning-Stout, Alison Kalett, Debra Liese, Donna Liese, Arthur Werneck, and Kimberley Williams from the Press for their efficiency in seeing the book through the publishing process.

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They learn to translate by reading millions of pages of (for example) multilingual European Union documents (they never get bored!). They learn to identify dogs, cats, and human faces by ‘crunching’ through millions of images viewed from different perspectives. Exciting advances have been spearheaded by DeepMind, a London company now owned by Google. DeepMind’s cofounder and CEO, Demis Hassabis, has had a precocious career. At thirteen he was ranked the number two chess champion in the world for his category. He qualified for admission to Cambridge at fifteen but delayed admission for two years, during which time he worked on computer games, including conceiving the highly successful Theme Park.

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In regard to all these post-2050 speculations, we don’t know where the boundary lies between what may happen and what will remain science fiction—just as we don’t know whether to take seriously Freeman Dyson’s vision of biohacking by children. There are widely divergent views. Some experts, for instance Stuart Russell at Berkeley, and Demis Hassabis of DeepMind, think that the AI field, like synthetic biotech, already needs guidelines for ‘responsible innovation’. Moreover, the fact that AlphaGo achieved a goal that its creators thought would have taken several more years to reach has rendered DeepMind’s staff even more bullish about the speed of advancement.

Outnumbered: From Facebook and Google to Fake News and Filter-Bubbles – the Algorithms That Control Our Lives by David Sumpter

affirmative action, algorithmic bias, AlphaGo, Bernie Sanders, Brexit referendum, Cambridge Analytica, classic study, cognitive load, Computing Machinery and Intelligence, correlation does not imply causation, crowdsourcing, data science, DeepMind, Demis Hassabis, disinformation, don't be evil, Donald Trump, Elon Musk, fake news, Filter Bubble, Geoffrey Hinton, Google Glasses, illegal immigration, James Webb Space Telescope, Jeff Bezos, job automation, Kenneth Arrow, Loebner Prize, Mark Zuckerberg, meta-analysis, Minecraft, Nate Silver, natural language processing, Nelson Mandela, Nick Bostrom, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, p-value, post-truth, power law, prediction markets, random walk, Ray Kurzweil, Robert Mercer, selection bias, self-driving car, Silicon Valley, Skype, Snapchat, social contagion, speech recognition, statistical model, Stephen Hawking, Steve Bannon, Steven Pinker, TED Talk, The Signal and the Noise by Nate Silver, traveling salesman, Turing test

The DeepMind team, which had won at Go and Space Invaders, has helped Google improve energy efficiency of its servers and developed more realistic speech for the company’s personal assistant. Another application area is DeepMind Health, a project one of the London Googlers had told me about when I visited them. The aim is to look at how the National Health Service in the UK collects and manages patient data in order to see how the process can be improved. DeepMind’s CEO Demis Hassabis talks about his team one day producing a ‘high-quality scientific paper where the first author is an AI’. The ultimate goal is to replace many of the difficult intellectual challenges carried out by engineers, doctors and scientists, with solutions created by intelligent machines. The researchers working on these projects often claim they are making small steps towards a more general artificial intelligence.

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At a meeting of the Future of Life Institute – a charitable organisation in Boston, Massachusetts, focused on dealing with future risks – in January 2017, theoretical physicist Max Tegmark hosted a panel debate about general artificial intelligence.1 The panel included nine of the most influential men in the field, including entrepreneur and Tesla CEO Elon Musk; the Google guru Ray Kurzweil; DeepMind’s founder Demis Hassabis and Nick Bostrom, the philosopher who has mapped our way to, what he calls, ‘superintelligence’. The panel members varied in their views as to whether human-level machine intelligence would come gradually or all of a sudden, or whether it will be good or bad for humanity. But they all agreed that a general form of AI was more or less inevitable.

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In another discussion at the same conference as Max Tegmark’s panel debate, Yan Le Cun, inventor of convolutional neural networks and Facebook’s lead AI researcher, described how solving the image-identification problem, using his method, had been like climbing over one mountain.4 Now they were over the top and back in a valley looking up at the next peak. Yan didn’t know how many more mountains there were to climb, but thought there could be ‘another 50’. DeepMind’s Demis Hassabis put the number of mountains at less than 20. In his view, these mountains each comprise a list of unsolved problems about how we simulate different, known properties of the brain.5 The mountain metaphor raises more questions than it answers. How do they know from looking at the next mountain if it can be conquered?

The Creativity Code: How AI Is Learning to Write, Paint and Think by Marcus Du Sautoy

3D printing, Ada Lovelace, Albert Einstein, algorithmic bias, AlphaGo, Alvin Roth, Andrew Wiles, Automated Insights, Benoit Mandelbrot, Bletchley Park, Cambridge Analytica, Charles Babbage, Claude Shannon: information theory, computer vision, Computing Machinery and Intelligence, correlation does not imply causation, crowdsourcing, data is the new oil, data science, deep learning, DeepMind, Demis Hassabis, Donald Trump, double helix, Douglas Hofstadter, driverless car, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, Flash crash, Gödel, Escher, Bach, Henri Poincaré, Jacquard loom, John Conway, Kickstarter, Loebner Prize, machine translation, mandelbrot fractal, Minecraft, move 37, music of the spheres, Mustafa Suleyman, Narrative Science, natural language processing, Netflix Prize, PageRank, pattern recognition, Paul Erdős, Peter Thiel, random walk, Ray Kurzweil, recommendation engine, Rubik’s Cube, Second Machine Age, Silicon Valley, speech recognition, stable marriage problem, Turing test, Watson beat the top human players on Jeopardy!, wikimedia commons

It set up a public contest with a huge prize and invited one of the world’s leading Go players to take up the challenge. An international champion, Lee Sedol from Korea, stepped forward. The competition would be played over five games with the winner taking home a prize of one million dollars. The name of Sedol’s challenger: AlphaGo. AlphaGo is the brainchild of Demis Hassabis. Hassabis was born in London in 1976 to a Greek Cypriot father and a mother from Singapore. Both parents are teachers and what Hassabis describes as bohemian technophobes. His sister and brother went the creative route, one becoming a composer, the other choosing creative writing. So Hassabis isn’t quite sure where his geeky scientific side came from.

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They were beginning to be more creative. These were the algorithms DeepMind exploited in its crushing of humanity in the game of Go. They ushered in the new age of machine learning. 5 FROM TOP DOWN TO BOTTOM UP Machines take me by surprise with great frequency. Alan Turing I first met Demis Hassabis a few years before his great Go triumph at a meeting about the future of innovation. New companies were on the lookout for investment from venture capitalists and investors. Some were going to transform the future, but most would flash and burn. The art was for VCs and angel investors to spot the winners.

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But despite the fact that these algorithms appear to have cracked the musical code, there is nothing stirring inside the machine. These are still our tools, the modern-day digital bullroarers. 13 DEEPMATHEMATICS It takes two to invent anything. The one makes up combinations, the other one chooses. Paul Valéry It was while sitting next to Demis Hassabis at one of the Royal Society’s meetings about the impact that machine learning was going to have on society that I had an idea. It was Hassabis’s algorithm AlphaGo that had started my whole existential crisis about whether the job of being a mathematician would continue to be a human one. Hassabis and I had both recently been made Fellows of the Royal Society, one of the highest accolades for a scientist.

Human Compatible: Artificial Intelligence and the Problem of Control by Stuart Russell

3D printing, Ada Lovelace, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Alfred Russel Wallace, algorithmic bias, AlphaGo, Andrew Wiles, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, basic income, behavioural economics, Bletchley Park, blockchain, Boston Dynamics, brain emulation, Cass Sunstein, Charles Babbage, Claude Shannon: information theory, complexity theory, computer vision, Computing Machinery and Intelligence, connected car, CRISPR, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, deep learning, deepfake, DeepMind, delayed gratification, Demis Hassabis, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ernest Rutherford, fake news, Flash crash, full employment, future of work, Garrett Hardin, Geoffrey Hinton, Gerolamo Cardano, Goodhart's law, Hans Moravec, ImageNet competition, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the wheel, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Nash: game theory, John von Neumann, Kenneth Arrow, Kevin Kelly, Law of Accelerating Returns, luminiferous ether, machine readable, machine translation, Mark Zuckerberg, multi-armed bandit, Nash equilibrium, Nick Bostrom, Norbert Wiener, NP-complete, OpenAI, openstreetmap, P = NP, paperclip maximiser, Pareto efficiency, Paul Samuelson, Pierre-Simon Laplace, positional goods, probability theory / Blaise Pascal / Pierre de Fermat, profit maximization, RAND corporation, random walk, Ray Kurzweil, Recombinant DNA, recommendation engine, RFID, Richard Thaler, ride hailing / ride sharing, Robert Shiller, robotic process automation, Rodney Brooks, Second Machine Age, self-driving car, Shoshana Zuboff, Silicon Valley, smart cities, smart contracts, social intelligence, speech recognition, Stephen Hawking, Steven Pinker, superintelligent machines, surveillance capitalism, Thales of Miletus, The Future of Employment, The Theory of the Leisure Class by Thorstein Veblen, Thomas Bayes, Thorstein Veblen, Tragedy of the Commons, transport as a service, trolley problem, Turing machine, Turing test, universal basic income, uranium enrichment, vertical integration, Von Neumann architecture, Wall-E, warehouse robotics, Watson beat the top human players on Jeopardy!, web application, zero-sum game

A history of Britain’s response to the re-emergence of AI in the 1980s: Brian Oakley and Kenneth Owen, Alvey: Britain’s Strategic Computing Initiative (MIT Press, 1990). 10. The origin of the term GOFAI: John Haugeland, Artificial Intelligence: The Very Idea (MIT Press, 1985). 11. Interview with Demis Hassabis on the future of AI and deep learning: Nick Heath, “Google DeepMind founder Demis Hassabis: Three truths about AI,” TechRepublic, September 24, 2018. APPENDIX C 1. Pearl’s work was recognized by the Turing Award in 2011. 2. Bayes nets in more detail: Every node in the network is annotated with the probability of each possible value, given each possible combination of values for the node’s parents (that is, those nodes that point to it).

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They epitomized what soon became a pejorative term: Good Old-Fashioned AI, or GOFAI.10 It became fashionable to dismiss logic as irrelevant to AI; indeed, many AI researchers working now in the area of deep learning don’t know anything about logic. This fashion seems likely to fade: if you accept that the world has objects in it that are related to each other in various ways, then first-order logic is going to be relevant, because it provides the basic mathematics of objects and relations. This view is shared by Demis Hassabis, CEO of Google DeepMind:11 You can think about deep learning as it currently is today as the equivalent in the brain to our sensory cortices: our visual cortex or auditory cortex. But, of course, true intelligence is a lot more than just that, you have to recombine it into higher-level thinking and symbolic reasoning, a lot of the things classical AI tried to deal with in the 80s. . . .

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There are further reasons to think that deep learning may reach a plateau well short of general intelligence, but it’s not my purpose here to diagnose all the problems: others, both inside8 and outside9 the deep learning community, have noted many of them. The point is that simply creating larger and deeper networks and larger data sets and bigger machines is not enough to create human-level AI. We have already seen (in Appendix B) DeepMind CEO Demis Hassabis’s view that “higher-level thinking and symbolic reasoning” are essential for AI. Another prominent deep learning expert, François Chollet, put it this way:10 “Many more applications are completely out of reach for current deep learning techniques—even given vast amounts of human-annotated data. . . .

Robot Rules: Regulating Artificial Intelligence by Jacob Turner

"World Economic Forum" Davos, Ada Lovelace, Affordable Care Act / Obamacare, AI winter, algorithmic bias, algorithmic trading, AlphaGo, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, autonomous vehicles, backpropagation, Basel III, bitcoin, Black Monday: stock market crash in 1987, blockchain, brain emulation, Brexit referendum, Cambridge Analytica, Charles Babbage, Clapham omnibus, cognitive dissonance, Computing Machinery and Intelligence, corporate governance, corporate social responsibility, correlation does not imply causation, crowdsourcing, data science, deep learning, DeepMind, Demis Hassabis, distributed ledger, don't be evil, Donald Trump, driverless car, easy for humans, difficult for computers, effective altruism, Elon Musk, financial exclusion, financial innovation, friendly fire, future of work, hallucination problem, hive mind, Internet of things, iterative process, job automation, John Markoff, John von Neumann, Loebner Prize, machine readable, machine translation, medical malpractice, Nate Silver, natural language processing, Nick Bostrom, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, nudge unit, obamacare, off grid, OpenAI, paperclip maximiser, pattern recognition, Peace of Westphalia, Philippa Foot, race to the bottom, Ray Kurzweil, Recombinant DNA, Rodney Brooks, self-driving car, Silicon Valley, Stanislav Petrov, Stephen Hawking, Steve Wozniak, strong AI, technological singularity, Tesla Model S, The Coming Technological Singularity, The Future of Employment, The Signal and the Noise by Nate Silver, trolley problem, Turing test, Vernor Vinge

For instance, automatic headlights which turn on at night would be mimicking the behaviour of a human being turning the lights on manually, but the behaviour would have been triggered by nothing more complex or mysterious than a light sensor coupled to simple logic gate.45 The 2011 Nevada definition was also under-inclusive because there are various emergent qualities that computer programs can display which go well beyond human capabilities. The manner in which humans solve problems is limited by the hardware available to us: our brains. AI has no such limits. DeepMind’s AlphaGo program achieved superhuman capabilities in Chess, Go, and other board games. DeepMind CEO Demis Hassabis explained: “It doesn’t play like a human, and it doesn’t play like a program, it plays in a third, almost alien, way”.46 At a sufficient point of advancement, it will no longer be accurate to describe AI as duplicating or mimicking the behaviour of humans—it will have surpassed us. 3.2 Rationalist Definitions More recent AI definitions avoid the link to humanity by focussing on thinking or acting rationally.

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Chapter 482A—Autonomous Vehicles, https://​www.​leg.​state.​nv.​us/​NRS/​NRS-482A.​html, accessed 1 June 2018. 45Ryan Calo, “Nevada Bill Would Pave the Road to Autonomous Cars”, Centre for Internet and Society Blog, 27 April 2011, http://​cyberlaw.​stanford.​edu/​blog/​2011/​04/​nevada-bill-would-pave-road-autonomous-cars, accessed 1 June 2018. 46Will Knight, “Alpha Zero’s “Alien” Chess Shows the Power, and the Peculiarity, of AI”, MIT Technology Review, https://​www.​technologyreview​.​com/​s/​609736/​alpha-zeros-alien-chess-shows-the-power-and-the-peculiarity-of-ai/​, accessed 1 June 2018. See for the academic paper: David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy Lillicrap, Karen Simonyan, and Demis Hassabis, “Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm”, Cornell University Library Research Paper, 5 December 2017, https://​arxiv.​org/​abs/​1712.​01815, accessed 1 June 2018. See also Cade Metz, What the AI Behind AlphaGo Can Teach Us About Being Human”, Wired, 19 May 2016, https://​www.​wired.​com/​2016/​05/​google-alpha-go-ai/​, accessed 1 June 2018. 47Russell and Norvig, Artificial Intelligence, para. 1.1. 48Nils J.

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See also the paper published by the DeepMind team: David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, and Demis Hassabis, “Mastering the Game of Go Without Human Knowledge”, Nature, Vol. 550 (19 October 2017), 354–359, https://​doi.​org/​10.​1038/​nature24270, accessed 1 June 2018. 131Silver et al., “AlphaGo Zero: Learning from Scratch”, DeepMind Website, 18 October 2017, https://​deepmind.​com/​blog/​alphago-zero-learning-scratch/​, accessed 1 June 2018. 132Matej Balog, Alexander L.

The Economic Singularity: Artificial Intelligence and the Death of Capitalism by Calum Chace

"World Economic Forum" Davos, 3D printing, additive manufacturing, agricultural Revolution, AI winter, Airbnb, AlphaGo, Alvin Toffler, Amazon Robotics, Andy Rubin, artificial general intelligence, augmented reality, autonomous vehicles, banking crisis, basic income, Baxter: Rethink Robotics, Berlin Wall, Bernie Sanders, bitcoin, blockchain, Boston Dynamics, bread and circuses, call centre, Chris Urmson, congestion charging, credit crunch, David Ricardo: comparative advantage, deep learning, DeepMind, Demis Hassabis, digital divide, Douglas Engelbart, Dr. Strangelove, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Fairchild Semiconductor, Flynn Effect, full employment, future of work, Future Shock, gender pay gap, Geoffrey Hinton, gig economy, Google Glasses, Google X / Alphabet X, Hans Moravec, Herman Kahn, hype cycle, 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, Kiva Systems, knowledge worker, lifelogging, lump of labour, Lyft, machine translation, Marc Andreessen, Mark Zuckerberg, Martin Wolf, McJob, means of production, Milgram experiment, Narrative Science, natural language processing, Neil Armstrong, new economy, Nick Bostrom, Occupy movement, Oculus Rift, OpenAI, PageRank, pattern recognition, post scarcity, post-industrial society, post-work, precariat, prediction markets, QWERTY keyboard, railway mania, RAND corporation, Ray Kurzweil, RFID, Rodney Brooks, Sam Altman, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, SoftBank, software is eating the world, speech recognition, Stephen Hawking, Steve Jobs, TaskRabbit, technological singularity, TED Talk, The future is already here, The Future of Employment, Thomas Malthus, transaction costs, Two Sigma, Tyler Cowen, Tyler Cowen: Great Stagnation, Uber for X, uber lyft, universal basic income, Vernor Vinge, warehouse automation, warehouse robotics, working-age population, Y Combinator, young professional

[ccxlii] Kris Hammond, the founder of Narrative Science whom we met when discussing journalists, says that “everybody thought [winning Jeopardy] was ridiculously impossible, [but now] it feels like they're putting a lot of things under the Watson brand name – but it isn't Watson.”[ccxliii] In March 2016, DeepMind founder Demis Hassabis went as far as to say that Watson is essentially an expert system as opposed to deep learning one.[ccxliv] IBM is unfazed by this kind of criticism. It says that Watson is now being used by hundreds of companies to solve particular problems – companies like the Australian energy group Woodside, which used it to review 20,000 documents from 30 years of engineering projects to identify, for instance, the maximum pressure that a certain type of pipeline can withstand.

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Ensuring that we survive that event is, I believe, the single most important task facing the next generation or two of humans – along with making sure we don’t blow ourselves up with nuclear weapons, or unleash a pathogen which kills everyone. If we secure the good outcome to the technological singularity, the future of humanity is glorious almost beyond imagination. As DeepMind co-founder Demis Hassabis likes to say, humanity’s plan for the future should consist of two steps: first, solve artificial general intelligence, and second, use that to solve everything else. “Everything else” includes poverty, illness, war and even death itself. The stakes in the economic singularity are not so high (which is why I tackled it second.)

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utm_content=bufferb9e5d&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer [ccxxxix] http://forbesindia.com/article/hidden-gems/thyrocare-technologies-testing-new-waters-in-medical-diagnostics/41051/1 [ccxl] http://www.ucsf.edu/news/2011/03/9510/new-ucsf-robotic-pharmacy-aims-improve-patient-safety [ccxli] http://www.qmed.com/news/ibms-watson-could-diagnose-cancer-better-doctors [ccxlii] http://www.ft.com/cms/s/2/dced8150-b300-11e5-8358-9a82b43f6b2f.html#axzz3xL3RoRdy [ccxliii] http://www.ft.com/cms/s/2/dced8150-b300-11e5-8358-9a82b43f6b2f.html#axzz3xL3RoRdy [ccxliv] http://www.theverge.com/2016/3/10/11192774/demis-hassabis-interview-alphago-google-deepmind-ai [ccxlv] http://qz.com/567658/searching-for-eureka-ibms-path-back-to-greatness-and-how-it-could-change-the-world/ [ccxlvi] http://www.forbes.com/sites/peterhigh/2016/01/18/ibm-watson-head-mike-rhodin-on-the-future-of-artificial-intelligence/#24204aab3e2922228b9c30cc [ccxlvii] http://www.dotmed.com/news/story/29020 [ccxlviii] http://www.wsj.com/articles/SB10001424052702303983904579093252573814132 [ccxlix] http://www.outpatientsurgery.net/outpatient-surgery-news-and-trends/general-surgical-news-and-reports/ethicon-pulling-sedasys-anesthesia-system--03-10-16 [ccl] http://www.wired.co.uk/news/archive/2016-05/05/autonomous-robot-surgeon [ccli] https://www.edsurge.com/news/2016-04-18-gradescope-raises-2-6m-to-apply-artificial-intelligence-to-grading-exams [cclii] http://www.wsj.com/articles/if-your-teacher-sounds-like-a-robot-you-might-be-on-to-something-1462546621 [ccliii] https://www.sigfig.com/site/#/home [ccliv] http://www.nytimes.com/2016/01/23/your-money/robo-advisers-for-investors-are-not-one-size-fits-all.html?

Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again by Eric Topol

"World Economic Forum" Davos, 23andMe, Affordable Care Act / Obamacare, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic bias, AlphaGo, Apollo 11, artificial general intelligence, augmented reality, autism spectrum disorder, autonomous vehicles, backpropagation, Big Tech, bioinformatics, blockchain, Cambridge Analytica, cloud computing, cognitive bias, Colonization of Mars, computer age, computer vision, Computing Machinery and Intelligence, conceptual framework, creative destruction, CRISPR, crowdsourcing, Daniel Kahneman / Amos Tversky, dark matter, data science, David Brooks, deep learning, DeepMind, Demis Hassabis, digital twin, driverless car, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, fake news, fault tolerance, gamification, general purpose technology, Geoffrey Hinton, George Santayana, Google Glasses, ImageNet competition, Jeff Bezos, job automation, job satisfaction, Joi Ito, machine translation, Mark Zuckerberg, medical residency, meta-analysis, microbiome, move 37, natural language processing, new economy, Nicholas Carr, Nick Bostrom, nudge unit, OpenAI, opioid epidemic / opioid crisis, pattern recognition, performance metric, personalized medicine, phenotype, placebo effect, post-truth, randomized controlled trial, recommendation engine, Rubik’s Cube, Sam Altman, self-driving car, Silicon Valley, Skinner box, speech recognition, Stephen Hawking, techlash, TED Talk, text mining, the scientific method, Tim Cook: Apple, traumatic brain injury, trolley problem, War on Poverty, Watson beat the top human players on Jeopardy!, working-age population

champions 2011—Speech recognition NN (Microsoft) 2012—University of Toronto ImageNet classification and cat video recognition (Google Brain, Andrew Ng, Jeff Dean) 2014—DeepFace facial recognition (Facebook) 2015—DeepMind vs. Atari (David Silver, Demis Hassabis) 2015—First AI risk conference (Max Tegmark) 2016—AlphaGo vs. Go (Silver, Demis Hassabis) 2017—AlphaGo Zero vs. Go (Silver, Demis Hassabis) 2017—Libratus vs. poker (Noam Brown, Tuomas Sandholm) 2017—AI Now Institute launched TABLE 4.2: The AI timeline. Kasparov’s book, Deep Thinking, which came out two decades later, provides remarkable personal insights about that pivotal AI turning point.

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The algorithm integrated a convolutional neural network with reinforcement learning, maneuvering a paddle to hit a brick on a wall.26 This qualified as a “holy shit” moment for Max Tegmark, as he recounted in his book Life 3.0: “The AI was simply told to maximize the score by outputting, at regular intervals, numbers which we (but not the AI) would recognize as codes for which keys to press.” According to DeepMind’s leader, Demis Hassabis, the strategy DeepMind learned to play was unknown to any human “until they learned it from the AI they’d built.” You could therefore interpret this as AI not only surpassing the video game performance of human professionals, but also of its creators. Many other video games have been taken on since, including forty-nine different Atari games.27 A year later, in 2016, DNN AI began taking on humans directly, when a program called AlphaGo triumphed over Lee Sodol, a world champion at the Chinese game of Go.

Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity by Daron Acemoglu, Simon Johnson

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 4chan, agricultural Revolution, AI winter, Airbnb, airline deregulation, algorithmic bias, algorithmic management, Alignment Problem, AlphaGo, An Inconvenient Truth, artificial general intelligence, augmented reality, basic income, Bellingcat, Bernie Sanders, Big Tech, Bletchley Park, blue-collar work, British Empire, carbon footprint, carbon tax, carried interest, centre right, Charles Babbage, ChatGPT, Clayton Christensen, clean water, cloud computing, collapse of Lehman Brothers, collective bargaining, computer age, Computer Lib, Computing Machinery and Intelligence, conceptual framework, contact tracing, Corn Laws, Cornelius Vanderbilt, coronavirus, corporate social responsibility, correlation does not imply causation, cotton gin, COVID-19, creative destruction, declining real wages, deep learning, DeepMind, deindustrialization, Demis Hassabis, Deng Xiaoping, deskilling, discovery of the americas, disinformation, Donald Trump, Douglas Engelbart, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, energy transition, Erik Brynjolfsson, European colonialism, everywhere but in the productivity statistics, factory automation, facts on the ground, fake news, Filter Bubble, financial innovation, Ford Model T, Ford paid five dollars a day, fulfillment center, full employment, future of work, gender pay gap, general purpose technology, Geoffrey Hinton, global supply chain, Gordon Gekko, GPT-3, Grace Hopper, Hacker Ethic, Ida Tarbell, illegal immigration, income inequality, indoor plumbing, industrial robot, interchangeable parts, invisible hand, Isaac Newton, Jacques de Vaucanson, James Watt: steam engine, Jaron Lanier, Jeff Bezos, job automation, Johannes Kepler, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph-Marie Jacquard, Kenneth Arrow, Kevin Roose, Kickstarter, knowledge economy, labor-force participation, land reform, land tenure, Les Trente Glorieuses, low skilled workers, low-wage service sector, M-Pesa, manufacturing employment, Marc Andreessen, Mark Zuckerberg, megacity, mobile money, Mother of all demos, move fast and break things, natural language processing, Neolithic agricultural revolution, Norbert Wiener, NSO Group, offshore financial centre, OpenAI, PageRank, Panopticon Jeremy Bentham, paperclip maximiser, pattern recognition, Paul Graham, Peter Thiel, Productivity paradox, profit maximization, profit motive, QAnon, Ralph Nader, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Robert Bork, Robert Gordon, Robert Solow, robotic process automation, Ronald Reagan, scientific management, Second Machine Age, self-driving car, seminal paper, shareholder value, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, social intelligence, Social Responsibility of Business Is to Increase Its Profits, social web, South Sea Bubble, speech recognition, spice trade, statistical model, stem cell, Steve Jobs, Steve Wozniak, strikebreaker, subscription business, Suez canal 1869, Suez crisis 1956, supply-chain management, surveillance capitalism, tacit knowledge, tech billionaire, technoutopianism, Ted Nelson, TED Talk, The Future of Employment, The Rise and Fall of American Growth, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, theory of mind, Thomas Malthus, too big to fail, total factor productivity, trade route, transatlantic slave trade, trickle-down economics, Turing machine, Turing test, Twitter Arab Spring, Two Sigma, Tyler Cowen, Tyler Cowen: Great Stagnation, union organizing, universal basic income, Unsafe at Any Speed, Upton Sinclair, upwardly mobile, W. E. B. Du Bois, War on Poverty, WikiLeaks, wikimedia commons, working poor, working-age population

Sundar Pichai, “AI is probably…,” is from https://money.cnn.com/2018/01/24/technology/sundar-pichai-google-ai-artificial-intelligence/index.html. Kai-Fu Lee, “AI could be…,” is from Lee (2021). Demis Hassabis, “[By] deepening our capacity,” is from https://theworldin.economist.com/edition/2020/article/17385/demis-hassabis-ais-potential; “Either we need…” is from www.techrepublic.com/article/google-deepmind-founder-demis-hassabis-three-truths-about-ai. “The intelligent revolution…” is from Li (2020). On Ray Kurzweil’s ideas, see Kurzweil (2005). Reid Hoffman, “Could we have a bad…,” is from www.city-journal.org/html/disrupters-14950.html.

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When all is said and done, the newfound enthusiasm about AI seems an intensification of the same optimism about technology, regardless of whether it focuses on the automation, surveillance, and disempowerment of ordinary people that had already engulfed the digital world. Yet these concerns are not taken seriously by most tech leaders. We are continuously told that AI will bring good. If it creates disruptions, those problems are short-term, inevitable, and easily rectified. If it is creating losers, the solution is more AI. For example, DeepMind’s cofounder, Demis Hassabis, not only thinks that AI “is going to be the most important technology ever invented,” but he is also confident that “by deepening our capacity to ask how and why, AI will advance the frontiers of knowledge and unlock whole new avenues of scientific discovery, improving the lives of billions of people.”

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The potential, therefore, is for truly pervasive use of AI in the economy and in our lives—for good but often also for bad. In the extreme, the aim becomes the development of completely autonomous, general intelligence, which can do everything that humans can do. In the words of DeepMind cofounder and CEO Demis Hassabis, the objective is “solving intelligence, and then using that to solve everything else.” But is this the best way to develop digital technologies? This question typically remains unasked. Third and more problematically, this approach has pushed the field even further in the direction of automation.

Elon Musk by Walter Isaacson

4chan, activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, AltaVista, Apollo 11, Apple II, Apple's 1984 Super Bowl advert, artificial general intelligence, autism spectrum disorder, autonomous vehicles, basic income, Big Tech, blockchain, Boston Dynamics, Burning Man, carbon footprint, ChatGPT, Chuck Templeton: OpenTable:, Clayton Christensen, clean tech, Colonization of Mars, computer vision, Computing Machinery and Intelligence, coronavirus, COVID-19, crowdsourcing, cryptocurrency, deep learning, DeepMind, Demis Hassabis, disinformation, Dogecoin, Donald Trump, Douglas Engelbart, drone strike, effective altruism, Elon Musk, estate planning, fail fast, fake news, game design, gigafactory, GPT-4, high-speed rail, hiring and firing, hive mind, Hyperloop, impulse control, industrial robot, information security, Jeff Bezos, Jeffrey Epstein, John Markoff, John von Neumann, Jony Ive, Kwajalein Atoll, lab leak, large language model, Larry Ellison, lockdown, low earth orbit, Marc Andreessen, Marc Benioff, Mars Society, Max Levchin, Michael Shellenberger, multiplanetary species, Neil Armstrong, Network effects, OpenAI, packet switching, Parler "social media", paypal mafia, peer-to-peer, Peter Thiel, QAnon, Ray Kurzweil, reality distortion field, remote working, rent control, risk tolerance, Rubik’s Cube, Salesforce, Sam Altman, Sam Bankman-Fried, San Francisco homelessness, Sand Hill Road, Saturday Night Live, self-driving car, seminal paper, short selling, Silicon Valley, Skype, SpaceX Starlink, Stephen Hawking, Steve Jobs, Steve Jurvetson, Steve Wozniak, Steven Levy, Streisand effect, supply-chain management, tech bro, TED Talk, Tesla Model S, the payments system, Tim Cook: Apple, universal basic income, Vernor Vinge, vertical integration, Virgin Galactic, wikimedia commons, William MacAskill, work culture , Y Combinator

“And if Thornfield Hall burns down and you are blind, I’ll come to you and take care of you.” 40 Artificial Intelligence OpenAI, 2012–2015 With Sam Altman Peter Thiel, the PayPal cofounder who had invested in SpaceX, holds a conference each year with the leaders of companies financed by his Founders Fund. At the 2012 gathering, Musk met Demis Hassabis, a neuroscientist, video-game designer, and artificial intelligence researcher with a courteous manner that conceals a competitive mind. A chess prodigy at age four, he became the five-time champion of an international Mind Sports Olympiad that includes competition in chess, poker, Mastermind, and backgammon.

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For a decade, Musk had been worried about the danger that artificial intelligence could someday run amok—develop a mind of its own, so to speak—and threaten humanity. When Google cofounder Larry Page dismissed his concerns, calling him a “specist” for favoring the human species over other forms of intelligence, it destroyed their friendship. Musk tried to prevent Page and Google from purchasing DeepMind, the company formed by AI pioneer Demis Hassabis. When that failed, he formed a competing lab, a nonprofit called OpenAI, with Sam Altman in 2015. Humans can be pricklier than machines, and Musk eventually split with Altman, left the board of OpenAI, and lured away its high-profile engineer Andrej Karpathy to lead the Autopilot team at Tesla.

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VP of flight reliability, SpaceX. Kunal Girotra. Former head of Tesla Energy. Juleanna Glover. Public relations consultant, Washington, DC. Antonio Gracias. Friend of Musk and investor. Michael Grimes. Managing director, Morgan Stanley. Trip Harriss. Manager of launch site operations, SpaceX. Demis Hassabis. Cofounder of DeepMind. Amber Heard. Actress, former girlfriend of Musk. Reid Hoffman. Cofounder of LinkedIn and PayPal. Ken Howery. Cofounder of PayPal and Musk friend. Lucas Hughes. Former finance director, SpaceX. Jared Isaacman. Entrepreneur and Inspiration4 commander. RJ Johnson. Former head of Tesla Energy.

The Industries of the Future by Alec Ross

"World Economic Forum" Davos, 23andMe, 3D printing, Airbnb, Alan Greenspan, algorithmic bias, algorithmic trading, AltaVista, Anne Wojcicki, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, bioinformatics, bitcoin, Black Lives Matter, blockchain, Boston Dynamics, Brian Krebs, British Empire, business intelligence, call centre, carbon footprint, clean tech, cloud computing, collaborative consumption, connected car, corporate governance, Credit Default Swap, cryptocurrency, data science, David Brooks, DeepMind, Demis Hassabis, disintermediation, Dissolution of the Soviet Union, distributed ledger, driverless car, Edward Glaeser, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, fiat currency, future of work, General Motors Futurama, global supply chain, Google X / Alphabet X, Gregor Mendel, industrial robot, information security, Internet of things, invention of the printing press, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Joi Ito, Kevin Roose, Kickstarter, knowledge economy, knowledge worker, lifelogging, litecoin, low interest rates, M-Pesa, machine translation, Marc Andreessen, Mark Zuckerberg, Max Levchin, Mikhail Gorbachev, military-industrial complex, mobile money, money: store of value / unit of account / medium of exchange, Nelson Mandela, new economy, off-the-grid, offshore financial centre, open economy, Parag Khanna, paypal mafia, 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, TED Talk, The Future of Employment, Travis Kalanick, underbanked, unit 8200, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, work culture , Y Combinator, young professional

The private sector is also investing: John Markoff, “Google Adds to Its Menagerie of Robots,” New York Times, December 14, 2013, http://www.nytimes.com/2013/12/14/technology/google-adds-to-its-menagerie-of-robots.html?_r=1&. As a kid, Hassabis was: Samuel Gibbs, “Demis Hassabis: 15 Facts about the DeepMind Technologies Founder,” Guardian, January 28, 2014, http://www.theguardian.com/technology/shortcuts/2014/jan/28/demis-hassabis-15-facts-deepmind-technologies-founder-google; “Breakthrough of the Year: The Runners-Up,” Science 318, no. 5858 (2007): 1844–49, doi:10.1126/science.318.5858.1844a. At DeepMind, Demis and his colleagues: “The Last AI Breakthrough DeepMind Made before Google Bought It for $400m,” Physics arXiv (Blog), https://medium.com/the-physics-arxiv-blog/the-last-ai-breakthrough-deepmind-made-before-google-bought-it-for-400m-7952031ee5e1.

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Sweden has similarly earmarked millions to give out to individuals and corporations through innovation awards such as Robotdalen (“robot valley”), launched in 2011. The private sector is also investing at increasingly higher levels. Google purchased Boston Dynamics, a leading robotics design company with Pentagon contracts, for an untold sum in December 2013. It also bought DeepMind, a London-based artificial intelligence company founded by wunderkind Demis Hassabis. As a kid, Hassabis was the second-highest-ranked chess player in the world under the age of 14, and while he was getting his PhD in cognitive neuroscience, he was acknowledged by Science magazine for making one of the ten most important science breakthroughs of the year after developing a new biological theory for how imagination and memory work in the brain.

Whiplash: How to Survive Our Faster Future by Joi Ito, Jeff Howe

3D printing, air gap, Albert Michelson, AlphaGo, Amazon Web Services, artificial general intelligence, basic income, Bernie Sanders, Big Tech, bitcoin, Black Lives Matter, Black Swan, Bletchley Park, blockchain, Burning Man, business logic, buy low sell high, Claude Shannon: information theory, cloud computing, commons-based peer production, Computer Numeric Control, conceptual framework, CRISPR, crowdsourcing, cryptocurrency, data acquisition, deep learning, DeepMind, Demis Hassabis, digital rights, disruptive innovation, Donald Trump, double helix, Edward Snowden, Elon Musk, Ferguson, Missouri, fiat currency, financial innovation, Flash crash, Ford Model T, frictionless, game design, Gerolamo Cardano, informal economy, information security, interchangeable parts, Internet Archive, Internet of things, Isaac Newton, Jeff Bezos, John Harrison: Longitude, Joi Ito, Khan Academy, Kickstarter, Mark Zuckerberg, microbiome, move 37, Nate Silver, Network effects, neurotypical, Oculus Rift, off-the-grid, One Laptop per Child (OLPC), PalmPilot, pattern recognition, peer-to-peer, pirate software, power law, pre–internet, prisoner's dilemma, Productivity paradox, quantum cryptography, race to the bottom, RAND corporation, random walk, Ray Kurzweil, Ronald Coase, Ross Ulbricht, Satoshi Nakamoto, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley startup, Simon Singh, Singularitarianism, Skype, slashdot, smart contracts, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, supply-chain management, synthetic biology, technological singularity, technoutopianism, TED Talk, The Nature of the Firm, the scientific method, The Signal and the Noise by Nate Silver, the strength of weak ties, There's no reason for any individual to have a computer in his home - Ken Olsen, Thomas Kuhn: the structure of scientific revolutions, Two Sigma, universal basic income, unpaid internship, uranium enrichment, urban planning, warehouse automation, warehouse robotics, Wayback Machine, WikiLeaks, Yochai Benkler

By the end of the day the big news wasn’t that AlphaGo had won a second game, but that it had displayed such deeply human qualities—improvisation, creativity, even a kind of grace—in doing so. The machine, we learned, had a soul. A few weeks after the conclusion of the Humans vs. Machines Showdown, Demis Hassabis—one of the artificial intelligence researchers behind Google’s DeepMind—gave a talk at MIT to discuss the match, and how his team had developed AlphaGo. Held in one of the university’s largest lecture halls, the DeepMind event drew a standing-room-only crowd—students were all but hanging off the walls to hear Hassabis describe how their approach to machine learning had allowed their team to prove the experts who had predicted it would take ten years for a computer to beat a virtuoso like Sedol wrong.

…

Thanks to John Seely Brown and John Hagel for The Power of Pull, and to my late adopted godfather, Timothy Leary, for being a “performing philosopher,” showing me how to be disobedient with style, and for “question authority and think for yourself.” Also Barack Obama for helping me with my messaging around “deploy.” Thanks to Seth Godin, J. J. Abrams, Walter Isaacson, Paola Antonelli, Vincenzo Iozzo, Jeremy Rubin, Ron Rivest, Scott E. Page, Mitch Resnick, Demis Hassabis, Sean Bonner, Colin Raney, Scott Hamilton, Ellen Hoffman, Natalie Saltiel, and many others for helping to review and revise the text. My executive assistant, Mika Tanaka, and former assistant Heather deManbey, who have had the thankless task of organizing my schedule and workflow throughout this process.

How to Fix the Future: Staying Human in the Digital Age by Andrew Keen

"World Economic Forum" Davos, 23andMe, Ada Lovelace, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, AlphaGo, Andrew Keen, Apple's 1984 Super Bowl advert, augmented reality, autonomous vehicles, basic income, Bernie Sanders, Big Tech, bitcoin, Black Swan, blockchain, Brewster Kahle, British Empire, carbon tax, Charles Babbage, computer age, Cornelius Vanderbilt, creative destruction, crowdsourcing, data is the new oil, death from overwork, DeepMind, Demis Hassabis, Didi Chuxing, digital capitalism, digital map, digital rights, disinformation, don't be evil, Donald Trump, driverless car, Edward Snowden, Elon Musk, Erik Brynjolfsson, European colonialism, fake news, Filter Bubble, Firefox, fulfillment center, full employment, future of work, gig economy, global village, income inequality, independent contractor, informal economy, Internet Archive, Internet of things, invisible hand, Isaac Newton, James Watt: steam engine, Jane Jacobs, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joi Ito, Kevin Kelly, knowledge economy, Lyft, Marc Andreessen, Marc Benioff, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Mitch Kapor, move fast and break things, Network effects, new economy, Nicholas Carr, Norbert Wiener, OpenAI, Parag Khanna, peer-to-peer, Peter Thiel, plutocrats, post-truth, postindustrial economy, precariat, Ralph Nader, Ray Kurzweil, Recombinant DNA, rent-seeking, ride hailing / ride sharing, Rutger Bregman, Salesforce, Sam Altman, Sand Hill Road, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Silicon Valley startup, Skype, smart cities, Snapchat, social graph, software is eating the world, Stephen Hawking, Steve Jobs, Steve Wozniak, subscription business, surveillance capitalism, Susan Wojcicki, tech baron, tech billionaire, tech worker, technological determinism, technoutopianism, The Future of Employment, the High Line, the new new thing, Thomas L Friedman, Tim Cook: Apple, Travis Kalanick, Triangle Shirtwaist Factory, Uber and Lyft, Uber for X, uber lyft, universal basic income, Unsafe at Any Speed, Upton Sinclair, urban planning, WikiLeaks, winner-take-all economy, Y Combinator, Yogi Berra, Zipcar

These kinds of ethical human judgments are critical, he says, if we are to maintain our control over smart machines. Yet for all his concerns about the demonic potential of artificial intelligence, Price isn’t entirely pessimistic about the future. He is encouraged, for example, by what he describes as the ethical maturity of the three cofounders of DeepMind, particularly Demis Hassabis, its young Cambridge-educated CEO. This is the London-based tech company whose investors include Jaan Tallinn and Elon Musk, a start-up founded in 2011 and then acquired by Google for $500 million in 2014. DeepMind made the headlines in March 2016 when AlphaGo, its specially designed algorithm, defeated a South Korean world champion Go player in this 5,500-year-old Chinese board game, the oldest and one of the most complex games ever invented by humans.

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We need to level up humans, because our descendants will either conquer the galaxy or extinguish consciousness in the universe forever,” he says, presenting this superintelligence threat as if it’s the plotline of a Star Trek episode.5 I ask Price what these young entrepreneurs, fabulously wealthy and gifted technologists like Deep Mind’s Demis Hassabis, or Y Combinator’s Sam Altman, need to incorporate into their self-prescribed moral code. What, I wonder, should the new men of the twenty-first century be thinking about to ensure that his Australian granddaughter will actually get to see the dawn of the twenty-second century? From where are these “moral criteria” going to come?

Know Thyself by Stephen M Fleming

Abraham Wald, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, AlphaGo, autism spectrum disorder, autonomous vehicles, availability heuristic, backpropagation, citation needed, computer vision, confounding variable, data science, deep learning, DeepMind, Demis Hassabis, Douglas Hofstadter, Dunning–Kruger effect, Elon Musk, Estimating the Reproducibility of Psychological Science, fake news, global pandemic, higher-order functions, index card, Jeff Bezos, l'esprit de l'escalier, Lao Tzu, lifelogging, longitudinal study, meta-analysis, mutually assured destruction, Network effects, patient HM, Pierre-Simon Laplace, power law, prediction markets, QWERTY keyboard, recommendation engine, replication crisis, self-driving car, side project, Skype, Stanislav Petrov, statistical model, theory of mind, Thomas Bayes, traumatic brain injury

Philosophical Transactions of the Royal Society B: Biological Sciences 366, no. 1566 (2011): 809–822. Sterling, Peter. “Allostasis: A Model of Predictive Regulation.” Physiology & Behavior 106, no. 1 (2012): 5–15. Stuss, D. T., M. P. Alexander, A. Lieberman, and H. Levine. “An Extraordinary Form of Confabulation.” Neurology 28, no. 11 (1978): 1166–1172. Summerfield, Jennifer J., Demis Hassabis, and Eleanor A. Maguire. “Cortical Midline Involvement in Autobiographical Memory.” NeuroImage 44, no. 3 (2009): 1188–1200. Sunstein, Cass R., Sebastian Bobadilla-Suarez, Stephanie C. Lazzaro, and Tali Sharot. “How People Update Beliefs About Climate Change: Good News and Bad News.” Cornell Law Review 102 (2016): 1431.

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“Neuroscience, Self-Understanding, and Narrative Truth.” AJOB Neuroscience 3, no. 4 (2012): 63–74. Wallis, Jonathan D. “Cross-Species Studies of Orbitofrontal Cortex and Value-Based Decision-Making.” Nature Neuroscience 15, no. 1 (2011): 13–19. Wang, Jane X., Zeb Kurth-Nelson, Dharshan Kumaran, Dhruva Tirumala, Hubert Soyer, Joel Z. Leibo, Demis Hassabis, and Matthew Botvinick. “Prefrontal Cortex as a Meta-Reinforcement Learning System.” Nature Neuroscience 21, no. 6 (2018): 860. Wegner, Daniel M. The Illusion of Conscious Will. Cambridge, MA: MIT Press, 2003. Weil, Leonora G., Stephen M. Fleming, Iroise Dumontheil, Emma J. Kilford, Rimona S.

Framers: Human Advantage in an Age of Technology and Turmoil by Kenneth Cukier, Viktor Mayer-Schönberger, Francis de Véricourt

Albert Einstein, Andrew Wiles, Apollo 11, autonomous vehicles, Ben Bernanke: helicopter money, Berlin Wall, bitcoin, Black Lives Matter, blockchain, Blue Ocean Strategy, circular economy, Claude Shannon: information theory, cognitive dissonance, cognitive load, contact tracing, coronavirus, correlation does not imply causation, COVID-19, credit crunch, CRISPR, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, deep learning, DeepMind, defund the police, Demis Hassabis, discovery of DNA, Donald Trump, double helix, Douglas Hofstadter, Elon Musk, en.wikipedia.org, fake news, fiat currency, framing effect, Francis Fukuyama: the end of history, Frank Gehry, game design, George Floyd, George Gilder, global pandemic, global village, Gödel, Escher, Bach, Higgs boson, Ignaz Semmelweis: hand washing, informal economy, Isaac Newton, Jaron Lanier, Jeff Bezos, job-hopping, knowledge economy, Large Hadron Collider, lockdown, Louis Pasteur, Mark Zuckerberg, Mercator projection, meta-analysis, microaggression, Mustafa Suleyman, Neil Armstrong, nudge unit, OpenAI, packet switching, pattern recognition, Peter Thiel, public intellectual, quantitative easing, Ray Kurzweil, Richard Florida, Schrödinger's Cat, scientific management, self-driving car, Silicon Valley, Steve Jobs, Steven Pinker, TED Talk, The Structural Transformation of the Public Sphere, Thomas Kuhn: the structure of scientific revolutions, TikTok, Tim Cook: Apple, too big to fail, transaction costs, Tyler Cowen

On the benefits of using data and statistics: Paul E. Meehl, Clinical Versus Statistical Prediction: A Theoretical Analysis and a Review of the Evidence (Minneapolis: University of Minnesota Press, 1954). On AlphaZero: This section benefited greatly from interviews in March 2019 by Kenneth Cukier with Demis Hassabis of DeepMind, as well as the chess grand master Matthew Sadler and master Natasha Regan, for which the authors extend their thanks. AlphaZero’s specifics on model training: David Silver et al., “A General Reinforcement Learning Algorithm That Masters Chess, Shogi and Go,” DeepMind, December 6, 2018, https://deepmind.com/blog/article/alphazero-shedding-new-light-grand-games-chess-shogi-and-go; David Silver et al., “Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm,” DeepMind, December 5, 2017, https://arxiv.org/pdf/1712.01815.pdf.

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Thanks also to Rimjhim Dey and the team at DEY, as well as Penguin and Dutton, for helping to promote the book. Many of the people who grace the pages took the time to speak with us. We thank, in alphabetical order, Andreas Altmann, Michael Baker, Regina Barzilay, Gérald Bronner, Ronald Burt, François Chollet, Daniel Dennett, Scott Donaldson, Inez Fung, Alison Gopnik, Peter Habeler, Demis Hassabis, Alan Kay, Tania Lombrozo, Heinz Machat, Gary Marcus, Robert Merton, Alyssa Milano, Alberto Moel, Nthabiseng Mosia, Scott Page, Judea Pearl, Sander Ruys, Peter Schwartz, Klaus Schweinsberg, Katrin Suder, Noam Tamir, Michael Tomasello, will.i.am (and Sallie Olmsted), and Apple’s communications team.

The Precipice: Existential Risk and the Future of Humanity by Toby Ord

3D printing, agricultural Revolution, Albert Einstein, Alignment Problem, AlphaGo, Anthropocene, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, availability heuristic, biodiversity loss, Columbian Exchange, computer vision, cosmological constant, CRISPR, cuban missile crisis, decarbonisation, deep learning, DeepMind, defense in depth, delayed gratification, Demis Hassabis, demographic transition, Doomsday Clock, Dr. Strangelove, Drosophila, effective altruism, Elon Musk, Ernest Rutherford, global pandemic, Goodhart's law, Hans Moravec, Herman Kahn, Higgs boson, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, James Watt: steam engine, Large Hadron Collider, launch on warning, Mark Zuckerberg, Mars Society, mass immigration, meta-analysis, Mikhail Gorbachev, mutually assured destruction, Nash equilibrium, Nick Bostrom, Norbert Wiener, nuclear winter, ocean acidification, OpenAI, p-value, Peter Singer: altruism, planetary scale, power law, public intellectual, race to the bottom, RAND corporation, Recombinant DNA, Ronald Reagan, self-driving car, seminal paper, social discount rate, Stanislav Petrov, Stephen Hawking, Steven Pinker, Stewart Brand, supervolcano, survivorship bias, synthetic biology, tacit knowledge, the scientific method, Tragedy of the Commons, uranium enrichment, William MacAskill

In part this is because progress may come very suddenly: through unpredictable research breakthroughs, or by rapid scaling-up of the first intelligent systems (for example by rolling them out to thousands of times as much hardware, or allowing them to improve their own intelligence).114 And in part it is because such a momentous change in human affairs may require more than a couple of decades to adequately prepare for. In the words of Demis Hassabis, co-founder of DeepMind: We need to use the downtime, when things are calm, to prepare for when things get serious in the decades to come. The time we have now is valuable, and we need to make use of it.115 DYSTOPIAN SCENARIOS So far we have focused on two kinds of existential catastrophe: extinction and the unrecoverable collapse of civilization.

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Thank you to Josie Axford-Foster, Beth Barnes, Nick Beckstead, Haydn Belfield, Nick Bostrom, Danny Bressler, Tim Campbell, Natalie Cargill, Shamil Chandaria, Paul Christiano, Teddy Collins, Owen Cotton-Barratt, Andrew Critch, Allan Dafoe, Max Daniel, Richard Danzig, Ben Delo, Daniel Dewey, Luke Ding, Peter Doane, Eric Drexler, Peter Eckersley, Holly Elmore, Sebastian Farquhar, Richard Fisher, Lukas Gloor, Ian Godfrey, Katja Grace, Hilary Greaves, Demis Hassabis, Hiski Haukkala, Alexa Hazel, Kirsten Horton, Holden Karnofsky, Lynn Keller, Luke Kemp, Alexis Kirschbaum, Howie Lempel, Gregory Lewis, Will MacAskill, Vishal Maini, Jason Matheny, Dylan Matthews, Tegan McCaslin, Andreas Mogensen, Luke Muehlhauser, Tim Munday, John Osborne, Richard Parr, Martin Rees, Sebastian Roberts, Max Roser, Anders Sandberg, Carl Shulman, Peter Singer, Andrew Snyder-Beattie, Pablo Stafforini, Jaan Tallinn, Christian Tarsney, Ben Todd, Susan Trammell, Brian Tse, Jonas Vollmer, Julia Wise and Bernadette Young.

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The only other community of researchers I can imagine who may have estimated such a high probability of their work leading to catastrophically bad outcomes for humanity are the atomic scientists in the lead-up to the bomb. And yet I’m grateful to the researchers for their frank honesty about this. 112 See, for example, Pinker in Enlightenment Now (2018, p. 300). 113 Demis Hassabis has addressed these issues explicitly (Bengio et al., 2017): “The coordination problem is one thing we should focus on now. We want to avoid this harmful race to the finish where corner-cutting starts happening and safety gets cut. That’s going to be a big issue on global scale.” 114 If systems could improve their own intelligence, there is a chance this would lead to a cascade called an “intelligence explosion.”

Life After Google: The Fall of Big Data and the Rise of the Blockchain Economy by George Gilder

23andMe, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, AlphaGo, AltaVista, Amazon Web Services, AOL-Time Warner, Asilomar, augmented reality, Ben Horowitz, bitcoin, Bitcoin Ponzi scheme, Bletchley Park, blockchain, Bob Noyce, British Empire, Brownian motion, Burning Man, business process, butterfly effect, carbon footprint, cellular automata, Claude Shannon: information theory, Clayton Christensen, cloud computing, computer age, computer vision, crony capitalism, cross-subsidies, cryptocurrency, Danny Hillis, decentralized internet, deep learning, DeepMind, Demis Hassabis, disintermediation, distributed ledger, don't be evil, Donald Knuth, Donald Trump, double entry bookkeeping, driverless car, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, fake news, fault tolerance, fiat currency, Firefox, first square of the chessboard, first square of the chessboard / second half of the chessboard, floating exchange rates, Fractional reserve banking, game design, Geoffrey Hinton, George Gilder, Google Earth, Google Glasses, Google Hangouts, index fund, inflation targeting, informal economy, initial coin offering, Internet of things, Isaac Newton, iterative process, Jaron Lanier, Jeff Bezos, Jim Simons, Joan Didion, John Markoff, John von Neumann, Julian Assange, Kevin Kelly, Law of Accelerating Returns, machine translation, Marc Andreessen, Mark Zuckerberg, Mary Meeker, means of production, Menlo Park, Metcalfe’s law, Money creation, money: store of value / unit of account / medium of exchange, move fast and break things, Neal Stephenson, Network effects, new economy, Nick Bostrom, Norbert Wiener, Oculus Rift, OSI model, PageRank, pattern recognition, Paul Graham, peer-to-peer, Peter Thiel, Ponzi scheme, prediction markets, quantitative easing, random walk, ransomware, Ray Kurzweil, reality distortion field, Recombinant DNA, Renaissance Technologies, Robert Mercer, Robert Metcalfe, Ronald Coase, Ross Ulbricht, Ruby on Rails, Sand Hill Road, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Singularitarianism, Skype, smart contracts, Snapchat, Snow Crash, software is eating the world, sorting algorithm, South Sea Bubble, speech recognition, Stephen Hawking, Steve Jobs, Steven Levy, Stewart Brand, stochastic process, Susan Wojcicki, TED Talk, telepresence, Tesla Model S, The Soul of a New Machine, theory of mind, Tim Cook: Apple, transaction costs, tulip mania, Turing complete, Turing machine, Vernor Vinge, Vitalik Buterin, Von Neumann architecture, Watson beat the top human players on Jeopardy!, WikiLeaks, Y Combinator, zero-sum game

Google was the recognized intellectual leader of the industry, and its AI ostentation was widely acclaimed. Indeed it signed up most of the world’s AI celebrities, including its spearheads of “deep learning” prowess, from Geoffrey Hinton and Andrew Ng to Jeff Dean, the beleaguered Anthony Levandowski, and Demis Hassabis of DeepMind. If Google had been a university, it would have utterly outshone all others in AI talent. It must have been discouraging, then, to find that Amazon had shrewdly captured much of the market for AI services with its 2014 Alexa and Echo projects. It launched actual hardware to bring AI to everyone’s household in the form of elegantly designed devices that answered questions and ordered products while eschewing ads.

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Here in early January 2017 many of the leading researchers and luminaries of the information age secretly gathered under the auspices of the Foundational Questions Institute, directed by the MIT physicist Max Tegmark and supported by tens of millions of dollars from Elon Musk and Skype’s co-founder Jaan Tallinn. The most prominent participants were the bright lights of Google: Larry Page, Eric Schmidt, Ray Kurzweil, Demis Hassabis, and Peter Norvig, along with former Googler Andrew Ng, later of Baidu and Stanford. Also there was Facebook’s Yann LeCun, an innovator in deep-learning math and a protégé of Google’s Geoffrey Hinton. A tenured contingent consisted of the technologist Stuart Russell, the philosopher David Chalmers, the catastrophe theorist Nick Bostrom, the nanotech prophet Eric Drexler, the cosmologist Lawrence Krauss, the economist Erik Brynjolfsson, and the “Singularitarian” Vernor Vinge, along with scores of other celebrity scientists.1 They gathered at Asilomar preparing to alert the world to the dire threat posed by . . . well, by themselves—Silicon Valley.

WTF?: What's the Future and Why It's Up to Us by Tim O'Reilly

"Friedman doctrine" OR "shareholder theory", 4chan, Affordable Care Act / Obamacare, Airbnb, AlphaGo, Alvin Roth, Amazon Mechanical Turk, Amazon Robotics, Amazon Web Services, AOL-Time Warner, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, basic income, behavioural economics, benefit corporation, Bernie Madoff, Bernie Sanders, Bill Joy: nanobots, bitcoin, Blitzscaling, blockchain, book value, Bretton Woods, Brewster Kahle, British Empire, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, carbon tax, Carl Icahn, Chuck Templeton: OpenTable:, Clayton Christensen, clean water, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, computer vision, congestion pricing, corporate governance, corporate raider, creative destruction, CRISPR, crowdsourcing, Danny Hillis, data acquisition, data science, deep learning, DeepMind, Demis Hassabis, Dennis Ritchie, deskilling, DevOps, Didi Chuxing, digital capitalism, disinformation, do well by doing good, Donald Davies, Donald Trump, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, fake news, Filter Bubble, Firefox, Flash crash, Free Software Foundation, fulfillment center, full employment, future of work, George Akerlof, gig economy, glass ceiling, Glass-Steagall Act, Goodhart's law, Google Glasses, Gordon Gekko, gravity well, greed is good, Greyball, Guido van Rossum, High speed trading, hiring and firing, Home mortgage interest deduction, Hyperloop, income inequality, independent contractor, index fund, informal economy, information asymmetry, Internet Archive, Internet of things, invention of movable type, invisible hand, iterative process, Jaron Lanier, Jeff Bezos, jitney, job automation, job satisfaction, John Bogle, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Zimmer (Lyft cofounder), Kaizen: continuous improvement, Ken Thompson, Kevin Kelly, Khan Academy, Kickstarter, Kim Stanley Robinson, knowledge worker, Kodak vs Instagram, Lao Tzu, Larry Ellison, Larry Wall, Lean Startup, Leonard Kleinrock, Lyft, machine readable, machine translation, Marc Andreessen, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, McMansion, microbiome, microservices, minimum viable product, mortgage tax deduction, move fast and break things, Network effects, new economy, Nicholas Carr, Nick Bostrom, obamacare, Oculus Rift, OpenAI, OSI model, Overton Window, packet switching, PageRank, pattern recognition, Paul Buchheit, peer-to-peer, peer-to-peer model, Ponzi scheme, post-truth, race to the bottom, Ralph Nader, randomized controlled trial, RFC: Request For Comment, Richard Feynman, Richard Stallman, ride hailing / ride sharing, Robert Gordon, Robert Metcalfe, Ronald Coase, Rutger Bregman, Salesforce, Sam Altman, school choice, Second Machine Age, secular stagnation, self-driving car, SETI@home, shareholder value, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart contracts, Snapchat, Social Responsibility of Business Is to Increase Its Profits, social web, software as a service, software patent, spectrum auction, speech recognition, Stephen Hawking, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, stock buybacks, strong AI, synthetic biology, TaskRabbit, telepresence, the built environment, the Cathedral and the Bazaar, The future is already here, The Future of Employment, the map is not the territory, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Davenport, Tony Fadell, Tragedy of the Commons, transaction costs, transcontinental railway, transportation-network company, Travis Kalanick, trickle-down economics, two-pizza team, Uber and Lyft, Uber for X, uber lyft, ubercab, universal basic income, US Airways Flight 1549, VA Linux, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, We are the 99%, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator, yellow journalism, zero-sum game, Zipcar

Google purchased DeepMind in 2014 for $500 million, after it demonstrated an AI that had learned to play various older Atari computer games simply by watching them being played. The highly publicized victory of AlphaGo over Lee Sedol, one of the top-ranked human Go players, represented a milestone for AI, because of the difficulty of the game and the impossibility of using brute-force analysis of every possible move. But DeepMind cofounder Demis Hassabis wrote, “We’re still a long way from a machine that can learn to flexibly perform the full range of intellectual tasks a human can—the hallmark of true artificial general intelligence.” Yann LeCun also blasted those who oversold the significance of AlphaGo’s victory, writing, “most of human and animal learning is unsupervised learning.

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No one even knows what such an intelligence might look like, but people like Nick Bostrom, Stephen Hawking, and Elon Musk postulate that once it exists, it will rapidly outstrip humanity, with unpredictable consequences. Bostrom calls this hypothetical next step in strong AI “artificial superintelligence.” Deep learning pioneers Demis Hassabis and Yann LeCun are skeptical. They believe we’re still a long way from artificial general intelligence. Andrew Ng, formerly the head of AI research for Chinese search giant Baidu, compared worrying about hostile AI of this kind to worrying about overpopulation on Mars. Even if we never achieve artificial general intelligence or artificial superintelligence, though, I believe that there is a third form of AI, which I call hybrid artificial intelligence, in which much of the near-term risk resides.

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Awakening,” New York Times Magazine, December 14, 2016, https://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html. 167 algorithmic detection of fake news: Jennifer Slegg, “Google Tackles Fake News, Inaccurate Content & Hate Sites in Rater Guidelines Update,” SEM Post, March 14, 2017, http://www.thesempost.com/google-tackles-fake-news-inaccurate-content-hate-sites-rater-guidelines-update/. 167 “directly from raw experience or data”: This claim has been removed from the deepmind.com website, but it can still be found via the Internet Archive. Retrieved March 28, 2016, https://web-beta.archive.org/web/20160328210752/https://deepmind.com/. 167 “the hallmark of true artificial general intelligence”: Demis Hassabis, “What We Learned in Seoul with AlphaGo,” Google Blog, March 16, 2016, https://blog.google/topics/machine-learning /what-we-learned-in-seoul-with-alphago/. 167 “getting to true AI”: Ben Rossi, “Google DeepMind’s AlphaGo Victory Not ‘True AI,’ Says Facebook’s AI Chief,” Information Age, March 14, 2016, http://www.information-age.com/google-deepminds-alphago-victory-not-true-ai-says-face books-ai-chief-123461099/. 169 “thinking about how to make people click ads”: Ashlee Vance, “This Tech Bubble Is Different,” Bloomberg Businessweek, April 14, 2011, https://www.bloomberg.com/news/articles/2011-04-14/this-tech-bubble-is-different.

MegaThreats: Ten Dangerous Trends That Imperil Our Future, and How to Survive Them by Nouriel Roubini

"World Economic Forum" Davos, 2021 United States Capitol attack, 3D printing, 9 dash line, AI winter, AlphaGo, artificial general intelligence, asset allocation, assortative mating, autonomous vehicles, bank run, banking crisis, basic income, Bear Stearns, Big Tech, bitcoin, Bletchley Park, blockchain, Boston Dynamics, Bretton Woods, British Empire, business cycle, business process, call centre, carbon tax, Carmen Reinhart, cashless society, central bank independence, collateralized debt obligation, Computing Machinery and Intelligence, coronavirus, COVID-19, creative destruction, credit crunch, crony capitalism, cryptocurrency, currency manipulation / currency intervention, currency peg, data is the new oil, David Ricardo: comparative advantage, debt deflation, decarbonisation, deep learning, DeepMind, deglobalization, Demis Hassabis, democratizing finance, Deng Xiaoping, disintermediation, Dogecoin, Donald Trump, Elon Musk, en.wikipedia.org, energy security, energy transition, Erik Brynjolfsson, Ethereum, ethereum blockchain, eurozone crisis, failed state, fake news, family office, fiat currency, financial deregulation, financial innovation, financial repression, fixed income, floating exchange rates, forward guidance, Fractional reserve banking, Francis Fukuyama: the end of history, full employment, future of work, game design, geopolitical risk, George Santayana, Gini coefficient, global pandemic, global reserve currency, global supply chain, GPS: selective availability, green transition, Greensill Capital, Greenspan put, Herbert Marcuse, high-speed rail, Hyman Minsky, income inequality, inflation targeting, initial coin offering, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of movable type, Isaac Newton, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, junk bonds, Kenneth Rogoff, knowledge worker, Long Term Capital Management, low interest rates, low skilled workers, low-wage service sector, M-Pesa, margin call, market bubble, Martin Wolf, mass immigration, means of production, meme stock, Michael Milken, middle-income trap, Mikhail Gorbachev, Minsky moment, Modern Monetary Theory, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, mortgage debt, Mustafa Suleyman, Nash equilibrium, natural language processing, negative equity, Nick Bostrom, non-fungible token, non-tariff barriers, ocean acidification, oil shale / tar sands, oil shock, paradox of thrift, pets.com, Phillips curve, planetary scale, Ponzi scheme, precariat, price mechanism, price stability, public intellectual, purchasing power parity, quantitative easing, race to the bottom, Ralph Waldo Emerson, ransomware, Ray Kurzweil, regulatory arbitrage, reserve currency, reshoring, Robert Shiller, Ronald Reagan, Salesforce, Satoshi Nakamoto, Savings and loan crisis, Second Machine Age, short selling, Silicon Valley, smart contracts, South China Sea, sovereign wealth fund, Stephen Hawking, TED Talk, The Great Moderation, the payments system, Thomas L Friedman, TikTok, too big to fail, Turing test, universal basic income, War on Poverty, warehouse robotics, Washington Consensus, Watson beat the top human players on Jeopardy!, working-age population, Yogi Berra, Yom Kippur War, zero-sum game, zoonotic diseases

“Distinguishing AI-generated text, images and audio from human generated will become extremely difficult,” says Mustafa Suleyman, a cofounder of DeepMind and till recently head of AI policy at Google, as the “transformers” revolution accelerates the power of AI.43 As a consequence, a large number of white-collar jobs using advanced levels of cognition will become obsolete. Humans won’t know that their counterparts are machines. When I met Demis Hassabis—the other cofounder of DeepMind—he compared the coming singularity to super intelligence that resembles ten thousand Einsteins solving any problem of science, medicine, technology, biology, or knowledge at the same time and in parallel. If that is the future, how can any human compete? Indeed, AI initially replaced routine jobs.

…

An intelligence explosion will occur when computers develop motivation to learn on their own at warp speed without human direction. There are no limits to how fast or how much they can learn and what new connections they will find. This is what singularity looks like. Human brains will resemble vacuum tubes in the era of printed circuits, severely limited in capacity. I asked Demis Hassabis whether ideas once relegated to science fiction look real. He predicts that we are only five major technological innovations and about twenty years away from the singularity. Unless humans merge with computers, writer Yuval Harari warns, Homo sapiens are finished. They will become obsolete just like Homo erectus, Homo habilus, and other early humans that have long since vanished.

A World Without Work: Technology, Automation, and How We Should Respond by Daniel Susskind

"World Economic Forum" Davos, 3D printing, agricultural Revolution, AI winter, Airbnb, Albert Einstein, algorithmic trading, AlphaGo, artificial general intelligence, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, Big Tech, blue-collar work, Boston Dynamics, British Empire, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, computer age, computer vision, computerized trading, creative destruction, David Graeber, David Ricardo: comparative advantage, deep learning, DeepMind, Demis Hassabis, demographic transition, deskilling, disruptive innovation, Donald Trump, Douglas Hofstadter, driverless car, drone strike, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, fake news, financial innovation, flying shuttle, Ford Model T, fulfillment center, future of work, gig economy, Gini coefficient, Google Glasses, Gödel, Escher, Bach, Hans Moravec, income inequality, income per capita, industrial robot, interchangeable parts, invisible hand, Isaac Newton, Jacques de Vaucanson, James Hargreaves, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joi Ito, Joseph Schumpeter, Kenneth Arrow, Kevin Roose, Khan Academy, Kickstarter, Larry Ellison, low skilled workers, lump of labour, machine translation, Marc Andreessen, Mark Zuckerberg, means of production, Metcalfe’s law, natural language processing, Neil Armstrong, Network effects, Nick Bostrom, Occupy movement, offshore financial centre, Paul Samuelson, Peter Thiel, pink-collar, precariat, purchasing power parity, Ray Kurzweil, ride hailing / ride sharing, road to serfdom, Robert Gordon, Sam Altman, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Snapchat, social intelligence, software is eating the world, sovereign wealth fund, spinning jenny, Stephen Hawking, Steve Jobs, strong AI, tacit knowledge, technological solutionism, TED Talk, telemarketer, The Future of Employment, The Rise and Fall of American Growth, the scientific method, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thorstein Veblen, Travis Kalanick, Turing test, Two Sigma, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, upwardly mobile, warehouse robotics, Watson beat the top human players on Jeopardy!, We are the 99%, wealth creators, working poor, working-age population, Y Combinator

The average salary for a developer in San Francisco, for example, is about $120,000 a year, while the best engineers are treated as superstars and receive pay packages to match.13 Today, when we recount economic history, we punctuate it with people like James Hargreaves, the inventor of the spinning jenny. In the future, when people tell the history of our own time, it will be filled with names like Demis Hassabis, of DeepMind, and other software engineers, as yet unknown. As for processing power, many of the new systems require extraordinarily powerful hardware to run effectively. Often, we take for granted quite how demanding even the most basic digital actions we carry out can be. A single Google search, for instance, requires as much processing power as the entire Apollo space program that put Neil Armstrong and eleven other astronauts on the moon—not simply the processing power used during the flights themselves, but all that was used during planning and execution for the seventeen launches across eleven years.14 Today’s cutting-edge technologies use far more power still.

…

See Autor, “Polanyi’s Paradox and the Shape of Employment Growth,” p. 130; and Dana Remus and Frank Levy, “Can Robots Be Lawyers? Computers, Lawyers, and the Practice of Law,” Georgetown Journal of Legal Ethics 30, no. 3 (2017): 501–58, available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2701092. 31.  See Demis Hassabis, “Artificial Intelligence: Chess Match of the Century,” Nature 544 (2017): 413–14. 32.  Cade Metz, “How Google’s AI Viewed the Move No Human Could Understand,” Wired, 14 March 2016. Also see Max Tegmark, Life 3.0: Being Human in the Age of Artificial Intelligence (London: Penguin Books, 2017), p. 87. 33.  

The Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma by Mustafa Suleyman

"World Economic Forum" Davos, 23andMe, 3D printing, active measures, Ada Lovelace, additive manufacturing, agricultural Revolution, AI winter, air gap, Airbnb, Alan Greenspan, algorithmic bias, Alignment Problem, AlphaGo, Alvin Toffler, Amazon Web Services, Anthropocene, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, ASML, autonomous vehicles, backpropagation, barriers to entry, basic income, benefit corporation, Big Tech, biodiversity loss, bioinformatics, Bletchley Park, Blitzscaling, Boston Dynamics, business process, business process outsourcing, call centre, Capital in the Twenty-First Century by Thomas Piketty, ChatGPT, choice architecture, circular economy, classic study, clean tech, cloud computing, commoditize, computer vision, coronavirus, corporate governance, correlation does not imply causation, COVID-19, creative destruction, CRISPR, critical race theory, crowdsourcing, cryptocurrency, cuban missile crisis, data science, decarbonisation, deep learning, deepfake, DeepMind, deindustrialization, dematerialisation, Demis Hassabis, disinformation, drone strike, drop ship, dual-use technology, Easter island, Edward Snowden, effective altruism, energy transition, epigenetics, Erik Brynjolfsson, Ernest Rutherford, Extinction Rebellion, facts on the ground, failed state, Fairchild Semiconductor, fear of failure, flying shuttle, Ford Model T, future of work, general purpose technology, Geoffrey Hinton, global pandemic, GPT-3, GPT-4, hallucination problem, hive mind, hype cycle, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, Internet of things, invention of the wheel, job automation, John Maynard Keynes: technological unemployment, John von Neumann, Joi Ito, Joseph Schumpeter, Kickstarter, lab leak, large language model, Law of Accelerating Returns, Lewis Mumford, license plate recognition, lockdown, machine readable, Marc Andreessen, meta-analysis, microcredit, move 37, Mustafa Suleyman, mutually assured destruction, new economy, Nick Bostrom, Nikolai Kondratiev, off grid, OpenAI, paperclip maximiser, personalized medicine, Peter Thiel, planetary scale, plutocrats, precautionary principle, profit motive, prompt engineering, QAnon, quantum entanglement, ransomware, Ray Kurzweil, Recombinant DNA, Richard Feynman, Robert Gordon, Ronald Reagan, Sam Altman, Sand Hill Road, satellite internet, Silicon Valley, smart cities, South China Sea, space junk, SpaceX Starlink, stealth mode startup, stem cell, Stephen Fry, Steven Levy, strong AI, synthetic biology, tacit knowledge, tail risk, techlash, techno-determinism, technoutopianism, Ted Kaczynski, the long tail, The Rise and Fall of American Growth, Thomas Malthus, TikTok, TSMC, Turing test, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, uranium enrichment, warehouse robotics, William MacAskill, working-age population, world market for maybe five computers, zero day

Here might be a tool, an impossible but extraordinary tool, to help us get through the awesome challenges of the decades ahead, from climate change to aging populations to sustainable food. With this in mind, in a quaint Regency-era office overlooking London’s Russell Square, I co-founded a company called DeepMind with two friends, Demis Hassabis and Shane Legg, in the summer of 2010. This was our goal, one that in retrospect still feels as ambitious and crazy and hopeful as it did back then: replicate the very thing that makes us unique as a species, our intelligence. To achieve this objective, we would need to create a system that could imitate and then eventually outperform all human cognitive abilities, from vision and speech to planning and imagination, and ultimately empathy and creativity.

…

A huge thanks to Gregory Allen, Graham Allison (and the faculty and staff of Harvard’s Belfer Center more widely), Sahar Amer, Anne Applebaum, Julian Baker, Samantha Barber, Gabriella Blum, Nick Bostrom, Ian Bremmer, Erik Brynjolfsson, Ben Buchanan, Sarah Carter, Rewon Child, George Church, Richard Danzig, Jennifer Doudna, Alexandra Eitel, Maria Eitel, Henry Elkus, Kevin Esvelt, Jeremy Fleming, Jack Goldsmith, Al Gore, Tristan Harris, Zaid Hassan, Jordan Hoffman, Joi Ito, Ayana Elizabeth Johnson, Danny Kahneman, Angela Kane, Melanie Katzman, Henry Kissinger, Kevin Klyman, Heinrich Küttler, Eric Lander, Sean Legassick, Aitor Lewkowycz, Leon Marshall, Jason Matheny, Andrew McAfee, Greg McKelvey, Dimitri Mehlhorn, David Miliband, Martha Minow, Geoff Mulgan, Aza Raskin, Tobias Rees, Stuart Russell, Jeffrey Sachs, Eric Schmidt, Bruce Schneier, Marilyn Thompson, Mayo Thompson, Thomas Viney, Maria Vogelauer, Mark Walport, Morwenna White, Scott Young, and Jonathan Zittrain. My co-founders of Inflection, Reid Hoffman and Karén Simonyan, for being wonderful collaborators. And my DeepMind co-founders, Demis Hassabis and Shane Legg, for their partnership over an extraordinary decade. Michael would like to thank his co-founders at Canelo, Iain Millar and Nick Barreto, for their ongoing support, but most of all his incredible wife, Dani, and sons, Monty and Dougie. NOTES For a bibliography of books consulted, please visit the website the-coming-wave.com/​bibliography.

Human Frontiers: The Future of Big Ideas in an Age of Small Thinking by Michael Bhaskar

"Margaret Hamilton" Apollo, 3D printing, additive manufacturing, AI winter, Albert Einstein, algorithmic trading, AlphaGo, Anthropocene, artificial general intelligence, augmented reality, autonomous vehicles, backpropagation, barriers to entry, basic income, behavioural economics, Benoit Mandelbrot, Berlin Wall, Big bang: deregulation of the City of London, Big Tech, Bletchley Park, blockchain, Boeing 747, brain emulation, Brexit referendum, call centre, carbon tax, charter city, citizen journalism, Claude Shannon: information theory, Clayton Christensen, clean tech, clean water, cognitive load, Columbian Exchange, coronavirus, cosmic microwave background, COVID-19, creative destruction, CRISPR, crony capitalism, cyber-physical system, dark matter, David Graeber, deep learning, DeepMind, deindustrialization, dematerialisation, Demis Hassabis, demographic dividend, Deng Xiaoping, deplatforming, discovery of penicillin, disruptive innovation, Donald Trump, double entry bookkeeping, Easter island, Edward Jenner, Edward Lorenz: Chaos theory, Elon Musk, en.wikipedia.org, endogenous growth, energy security, energy transition, epigenetics, Eratosthenes, Ernest Rutherford, Eroom's law, fail fast, false flag, Fellow of the Royal Society, flying shuttle, Ford Model T, Francis Fukuyama: the end of history, general purpose technology, germ theory of disease, glass ceiling, global pandemic, Goodhart's law, Google Glasses, Google X / Alphabet X, GPT-3, Haber-Bosch Process, hedonic treadmill, Herman Kahn, Higgs boson, hive mind, hype cycle, Hyperloop, Ignaz Semmelweis: hand washing, Innovator's Dilemma, intangible asset, interchangeable parts, Internet of things, invention of agriculture, invention of the printing press, invention of the steam engine, invention of the telegraph, invisible hand, Isaac Newton, ITER tokamak, James Watt: steam engine, James Webb Space Telescope, Jeff Bezos, jimmy wales, job automation, Johannes Kepler, John von Neumann, Joseph Schumpeter, Kenneth Arrow, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, Large Hadron Collider, liberation theology, lockdown, lone genius, loss aversion, Louis Pasteur, Mark Zuckerberg, Martin Wolf, megacity, megastructure, Menlo Park, Minecraft, minimum viable product, mittelstand, Modern Monetary Theory, Mont Pelerin Society, Murray Gell-Mann, Mustafa Suleyman, natural language processing, Neal Stephenson, nuclear winter, nudge unit, oil shale / tar sands, open economy, OpenAI, opioid epidemic / opioid crisis, PageRank, patent troll, Peter Thiel, plutocrats, post scarcity, post-truth, precautionary principle, public intellectual, publish or perish, purchasing power parity, quantum entanglement, Ray Kurzweil, remote working, rent-seeking, Republic of Letters, Richard Feynman, Robert Gordon, Robert Solow, secular stagnation, shareholder value, Silicon Valley, Silicon Valley ideology, Simon Kuznets, skunkworks, Slavoj Žižek, sovereign wealth fund, spinning jenny, statistical model, stem cell, Steve Jobs, Stuart Kauffman, synthetic biology, techlash, TED Talk, The Rise and Fall of American Growth, the scientific method, The Wealth of Nations by Adam Smith, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, TikTok, total factor productivity, transcontinental railway, Two Sigma, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, uranium enrichment, We wanted flying cars, instead we got 140 characters, When a measure becomes a target, X Prize, Y Combinator

The headlines were breathless: Nature said ‘It will change everything’, Science that ‘the game has changed’.8 If anything AlQuraishi was even more stunned than before, blogging that the problem he'd spent his life trying to solve was now potentially done, leaving him feeling like a child had left the family home.9 ‘It's a breakthrough of the first order, certainly one of the most significant scientific results of my lifetime,’ he said. A fifty-year grand scientific challenge was over, a new realm of biological possibility and understanding broached by the latest AI techniques. AI is already re-accelerating scientific discovery. Demis Hassabis, the co-founder and CEO of DeepMind, talks about this aspect of AI. As he argues, ‘The promise of AI is that it could serve as an extension of our minds and become a meta-solution,’ and in doing so help ‘usher in a new renaissance of discovery, acting as a multiplier for human ingenuity, opening up entirely new areas of inquiry’.10 Our tools, and the potential they embody, are not standing still.

…

Without its toolkit, the Scientific Revolution – not to mention the Reformation and Renaissance – would look very different. This is true of everything since – tools and ideas work in tandem.19 In the twenty-first century our capacity to develop big ideas will rest on the development of our tools more than any other factor. Hence the significance of AI. It is the calculus, the telescope, the compass of our time. Demis Hassabis himself makes the link explicit, calling AI a sort of general-purpose Hubble space telescope for science.20 Big ideas like AlphaFold and AlphaGo, instances of the big idea of deep learning neural networks, are steadily making a difference at the coalface. To see how AI reshapes ideas, consider the volume of data produced by contemporary experiments.

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

Adam Curtis, agricultural Revolution, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, Anthropocene, artificial general intelligence, augmented reality, autism spectrum disorder, autonomous vehicles, backpropagation, basic income, behavioural economics, bitcoin, blockchain, bread and circuses, Charles Babbage, 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, data science, deep learning, DeepMind, Demis Hassabis, digital capitalism, digital divide, digital rights, discrete time, Douglas Engelbart, driverless car, Elon Musk, Emanuel Derman, endowment effect, epigenetics, Ernest Rutherford, experimental economics, financial engineering, Flash crash, friendly AI, functional fixedness, global pandemic, Google Glasses, Great Leap Forward, Hans Moravec, hive mind, Ian Bogost, income inequality, information trail, Internet of things, invention of writing, iterative process, James Webb Space Telescope, Jaron Lanier, job automation, Johannes Kepler, John Markoff, John von Neumann, Kevin Kelly, knowledge worker, Large Hadron Collider, lolcat, loose coupling, machine translation, microbiome, mirror neurons, Moneyball by Michael Lewis explains big data, Mustafa Suleyman, natural language processing, Network effects, Nick Bostrom, Norbert Wiener, paperclip maximiser, pattern recognition, Peter Singer: altruism, phenotype, planetary scale, Ray Kurzweil, Recombinant DNA, 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, social intelligence, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, superintelligent machines, supervolcano, synthetic biology, systems thinking, tacit knowledge, TED Talk, 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!, We are as Gods, Y2K

MELANIE SWAN The Future Possibility-Space of Intelligence TOR NØRRETRANDERS Love KAI KRAUSE An Uncanny Three-Ring Test for Machina sapiens GEORG DIEZ Free from Us EDUARDO SALCEDO-ALBARÁN Flawless AI Seems Like Science Fiction MARIA SPIROPULU Emergent Hybrid Human/Machine Chimeras THOMAS METZINGER What If They Need to Suffer? BEATRICE GOLOMB Will We Recognize It When It Happens? NOGA ARIKHA Metarepresentation DEMIS HASSABIS, SHANE LEGG & MUSTAFA SULEYMAN Envoi: A Short Distance Ahead—and Plenty to Be Done NOTES ABOUT THE AUTHOR ALSO BY JOHN BROCKMAN CREDITS BACK ADS COPYRIGHT ABOUT THE PUBLISHER ACKNOWLEDGMENTS My thanks to Peter Hubbard of HarperCollins and my agent, Max Brockman, for their continued encouragement.

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They’re good at tasks, and we’ve become good at using them for our purposes. But until we replicate the embodied emotional being—a feat I don’t believe we can achieve—our machines will continue to serve as occasional analogies for thought and to evolve according to our needs. ENVOI: A SHORT DISTANCE AHEAD—AND PLENTY TO BE DONE DEMIS HASSABIS Vice President of Engineering, Google DeepMind; cofounder, DeepMind Technologies SHANE LEGG AI researcher; cofounder, DeepMind Technologies MUSTAFA SULEYMAN Head of applied AI, Google DeepMind; cofounder, DeepMind Technologies For years we’ve been making the case that artificial intelligence, and in particular the field of machine learning, is making rapid progress and is set to make a whole lot more progress.

The Future We Choose: Surviving the Climate Crisis by Christiana Figueres, Tom Rivett-Carnac

3D printing, Airbnb, AlphaGo, Anthropocene, autonomous vehicles, Berlin Wall, biodiversity loss, carbon footprint, circular economy, clean water, David Attenborough, decarbonisation, DeepMind, dematerialisation, Demis Hassabis, disinformation, Donald Trump, driverless car, en.wikipedia.org, Extinction Rebellion, F. W. de Klerk, Fall of the Berlin Wall, Gail Bradbrook, General Motors Futurama, green new deal, Greta Thunberg, high-speed rail, income inequality, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jeff Bezos, job automation, Lyft, Mahatma Gandhi, Marc Benioff, Martin Wolf, mass immigration, Mustafa Suleyman, Nelson Mandela, new economy, ocean acidification, plant based meat, post-truth, rewilding, ride hailing / ride sharing, self-driving car, smart grid, sovereign wealth fund, the scientific method, trade route, uber lyft, urban planning, urban sprawl, Yogi Berra

World Bank, “Accounting Reveals That Costa Rica’s Forest Wealth Is Greater Than Expected,” May 31, 2016, https://www.worldbank.org/​en/​news/​feature/​2016/​05/​31/​accounting-reveals-that-costa-ricas-forest-wealth-is-greater-than-expected. 73. See http://happyplanetindex.org/​countries/​costa-rica. 74. For a helpful introduction to AI, see Snips, “A 6-Minute Intro to AI,” https://snips.ai/​content/​intro-to-ai/​#ai-metrics. 75. David Silver and Demis Hassabis, “AlphaGo Zero: Starting from Scratch,” DeepMind, October 18, 2017, https://deepmind.com/​blog/​alphago-zero-learning-scratch/. 76. DeepMind, https://deepmind.com/. 77. Rupert Neate, “Richest 1% Own Half the World’s Wealth, Study Finds,” Guardian (U.S. edition), November 14, 2017, https://www.theguardian.com/​inequality/​2017/​nov/​14/​worlds-richest-wealth-credit-suisse. 78.

Survival of the Richest: Escape Fantasies of the Tech Billionaires by Douglas Rushkoff

"World Economic Forum" Davos, 4chan, A Declaration of the Independence of Cyberspace, agricultural Revolution, Airbnb, Alan Greenspan, Amazon Mechanical Turk, Amazon Web Services, Andrew Keen, AOL-Time Warner, artificial general intelligence, augmented reality, autonomous vehicles, basic income, behavioural economics, Big Tech, biodiversity loss, Biosphere 2, bitcoin, blockchain, Boston Dynamics, Burning Man, buy low sell high, Californian Ideology, carbon credits, carbon footprint, circular economy, clean water, cognitive dissonance, Colonization of Mars, coronavirus, COVID-19, creative destruction, Credit Default Swap, CRISPR, data science, David Graeber, DeepMind, degrowth, Demis Hassabis, deplatforming, digital capitalism, digital map, disinformation, Donald Trump, Elon Musk, en.wikipedia.org, energy transition, Ethereum, ethereum blockchain, European colonialism, Evgeny Morozov, Extinction Rebellion, Fairphone, fake news, Filter Bubble, game design, gamification, gig economy, Gini coefficient, global pandemic, Google bus, green new deal, Greta Thunberg, Haight Ashbury, hockey-stick growth, Howard Rheingold, if you build it, they will come, impact investing, income inequality, independent contractor, Jane Jacobs, Jeff Bezos, Jeffrey Epstein, job automation, John Nash: game theory, John Perry Barlow, Joseph Schumpeter, Just-in-time delivery, liberal capitalism, Mark Zuckerberg, Marshall McLuhan, mass immigration, megaproject, meme stock, mental accounting, Michael Milken, microplastics / micro fibres, military-industrial complex, Minecraft, mirror neurons, move fast and break things, Naomi Klein, New Urbanism, Norbert Wiener, Oculus Rift, One Laptop per Child (OLPC), operational security, Patri Friedman, pattern recognition, Peter Thiel, planetary scale, Plato's cave, Ponzi scheme, profit motive, QAnon, RAND corporation, Ray Kurzweil, rent-seeking, Richard Thaler, ride hailing / ride sharing, Robinhood: mobile stock trading app, Sam Altman, Shoshana Zuboff, Silicon Valley, Silicon Valley billionaire, SimCity, Singularitarianism, Skinner box, Snapchat, sovereign wealth fund, Stephen Hawking, Steve Bannon, Steve Jobs, Steven Levy, Steven Pinker, Stewart Brand, surveillance capitalism, tech billionaire, tech bro, technological solutionism, technoutopianism, Ted Nelson, TED Talk, the medium is the message, theory of mind, TikTok, Torches of Freedom, Tragedy of the Commons, universal basic income, urban renewal, warehouse robotics, We are as Gods, WeWork, Whole Earth Catalog, work culture , working poor

The bigger the billionaire, the greater the fear, and the countermeasures. Elon Musk told a 2014 audience at MIT that by experimenting with AI, Larry Page and his friends at Google are “summoning the demon .” In a now famous Vanity Fair account of a conversation between Elon Musk and DeepMind creator Demis Hassabis, Musk explained that one of the reasons he intended to colonize Mars was “so that we’ll have a bolt-hole if AI goes rogue and turns on humanity.” Similarly, Musk has been developing a neural net apparatus that can be lasered onto our brains, which would potentially allow us to compete with a superintelligent rogue AI that turns against us.

The Science of Storytelling: Why Stories Make Us Human, and How to Tell Them Better by Will Storr

data science, David Brooks, Demis Hassabis, Gordon Gekko, heat death of the universe, meta-analysis, Steven Pinker, TED Talk, theory of mind, Wall-E

Bergen (Basic, 2012) p. 99. For the same reason, active sentence construction: Louder than Words, Benjamin K. Bergen (Basic, 2012) p. 119. to make vivid scenes, three specific qualities: ‘Differential engagement of brain regions within a “core” network during scene construction’, Jennifer Summerfield, Demis Hassabis & Eleanor Maguire, Neuropsychologia, 2010, Vol. 48, 1501–1509. As C. S. Lewis implored a young writer in 1956: http://www.lettersofnote.com/2012/04/c-s-lewis-on-writing.html Only that way: A final lesson from the model-making brain is that simplicity is also crucial. The human beam of attention is narrow.

Work in the Future The Automation Revolution-Palgrave MacMillan (2019) by Robert Skidelsky Nan Craig

3D printing, Airbnb, algorithmic trading, AlphaGo, Alvin Toffler, Amazon Web Services, anti-work, antiwork, artificial general intelligence, asset light, autonomous vehicles, basic income, behavioural economics, business cycle, cloud computing, collective bargaining, Computing Machinery and Intelligence, correlation does not imply causation, creative destruction, data is the new oil, data science, David Graeber, David Ricardo: comparative advantage, deep learning, DeepMind, deindustrialization, Demis Hassabis, deskilling, disintermediation, do what you love, Donald Trump, driverless car, Erik Brynjolfsson, fake news, feminist movement, Ford Model T, Frederick Winslow Taylor, future of work, Future Shock, general purpose technology, gig economy, global supply chain, income inequality, independent contractor, informal economy, Internet of things, Jarndyce and Jarndyce, Jarndyce and Jarndyce, job automation, job polarisation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, knowledge economy, Loebner Prize, low skilled workers, Lyft, Mark Zuckerberg, means of production, moral panic, Network effects, new economy, Nick Bostrom, off grid, pattern recognition, post-work, Ronald Coase, scientific management, Second Machine Age, self-driving car, sharing economy, SoftBank, Steve Jobs, strong AI, tacit knowledge, technological determinism, technoutopianism, TED Talk, The Chicago School, The Future of Employment, the market place, The Nature of the Firm, The Wealth of Nations by Adam Smith, Thorstein Veblen, Turing test, Uber for X, uber lyft, universal basic income, wealth creators, working poor

In addition, concerns were raised about my point that the majority of AI researchers tend to separate development of AI technology from its uses and not worry too much about ethical issues. I emphasized that while this is currently the case, things are changing, with technology leaders such as Demis Hassabis from Google Deep Mind promoting ethical usage of AI, and ethics courses being given to computing students. Later, we returned to the question of who makes the decisions about AI usage, and discussed whether this is likely to come from the bottom up, for example from community or consumer groups, and I confessed to being dubious about this.

Final Jeopardy: Man vs. Machine and the Quest to Know Everything by Stephen Baker

23andMe, AI winter, Albert Einstein, artificial general intelligence, behavioural economics, business process, call centre, clean water, commoditize, computer age, Demis Hassabis, Frank Gehry, information retrieval, Iridium satellite, Isaac Newton, job automation, machine translation, pattern recognition, Ray Kurzweil, Silicon Valley, Silicon Valley startup, statistical model, The Soul of a New Machine, theory of mind, thinkpad, Turing test, Vernor Vinge, vertical integration, Wall-E, Watson beat the top human players on Jeopardy!

No one was close to replicating the brain in form or function. Still, the scientists at the conference were busy studying it, hoping to glean from its workings single applications that could be taught to computers. The brain, they held, would deliver its treasures bit by bit. Tenenbaum was of this school. And so was Demis Hassabis. A diminutive thirty-four-year-old British neuroscientist, Hassabis told the crowd that technology wasn’t the only thing growing exponentially. Research papers on the brain were also doubling every year. Some fifty thousand academic papers on neuroscience had been published in 2008 alone. “If you looked at neuroscience in 2005, or before that, you’re way out of date now,” he said.

The Smartphone Society by Nicole Aschoff

"Susan Fowler" uber, 4chan, A Declaration of the Independence of Cyberspace, Airbnb, algorithmic bias, algorithmic management, Amazon Web Services, artificial general intelligence, autonomous vehicles, barriers to entry, Bay Area Rapid Transit, Bernie Sanders, Big Tech, Black Lives Matter, blockchain, carbon footprint, Carl Icahn, Cass Sunstein, citizen journalism, cloud computing, correlation does not imply causation, crony capitalism, crowdsourcing, cryptocurrency, data science, deep learning, DeepMind, degrowth, Demis Hassabis, deplatforming, deskilling, digital capitalism, digital divide, do what you love, don't be evil, Donald Trump, Downton Abbey, Edward Snowden, Elon Musk, Evgeny Morozov, fake news, feminist movement, Ferguson, Missouri, Filter Bubble, financial independence, future of work, gamification, gig economy, global value chain, Google Chrome, Google Earth, Googley, green new deal, housing crisis, income inequality, independent contractor, Jaron Lanier, Jeff Bezos, Jessica Bruder, job automation, John Perry Barlow, knowledge economy, late capitalism, low interest rates, Lyft, M-Pesa, Mark Zuckerberg, minimum wage unemployment, mobile money, moral panic, move fast and break things, Naomi Klein, Network effects, new economy, Nicholas Carr, Nomadland, occupational segregation, Occupy movement, off-the-grid, offshore financial centre, opioid epidemic / opioid crisis, PageRank, Patri Friedman, peer-to-peer, Peter Thiel, pets.com, planned obsolescence, quantitative easing, Ralph Waldo Emerson, RAND corporation, Ray Kurzweil, RFID, Richard Stallman, ride hailing / ride sharing, Rodney Brooks, Ronald Reagan, Salesforce, Second Machine Age, self-driving car, shareholder value, sharing economy, Sheryl Sandberg, Shoshana Zuboff, Sidewalk Labs, Silicon Valley, single-payer health, Skype, Snapchat, SoftBank, statistical model, Steve Bannon, Steve Jobs, surveillance capitalism, TaskRabbit, tech worker, technological determinism, TED Talk, the scientific method, The Structural Transformation of the Public Sphere, TikTok, transcontinental railway, transportation-network company, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, upwardly mobile, Vision Fund, W. E. B. Du Bois, wages for housework, warehouse robotics, WikiLeaks, women in the workforce, yottabyte

Self-driving cars and the ability of the Alpha Go Zero program to teach itself how to play the ancient and extremely difficult Chinese game of Go using only the game rules and reinforcement learning are just the beginning of a seismic shift rooted in the power of data. The motto of Alphabet subsidiary DeepMind encapsulates this vision of the future: “Solve intelligence and use that to solve everything else.” Run by Demis Hassabis, a neuroscientist, video game developer, and former child chess prodigy, and a team of about two hundred computer scientists and neuroscientists, the Alphabet subsidiary’s researchers have operationalized the idea that intelligence, thought, and perhaps even consciousness are nothing more than a collection of discrete, local processes that can be “solved” with enough computing power and data.

Thinking in Bets by Annie Duke

banking crisis, behavioural economics, Bernie Madoff, Cass Sunstein, cognitive bias, cognitive dissonance, cognitive load, Daniel Kahneman / Amos Tversky, delayed gratification, Demis Hassabis, disinformation, Donald Trump, Dr. Strangelove, en.wikipedia.org, endowment effect, Estimating the Reproducibility of Psychological Science, fake news, Filter Bubble, Herman Kahn, hindsight bias, Jean Tirole, John Nash: game theory, John von Neumann, loss aversion, market design, mutually assured destruction, Nate Silver, p-value, phenotype, prediction markets, Richard Feynman, ride hailing / ride sharing, Stanford marshmallow experiment, Stephen Hawking, Steven Pinker, systematic bias, TED Talk, the scientific method, The Signal and the Noise by Nate Silver, urban planning, Walter Mischel, Yogi Berra, zero-sum game

“The Evolutionary Roots of Human Decision Making.” Annual Review of Psychology 66 (January 2015): 321–47. Savage, David. “Clarence Thomas Is His Own Man.” Los Angeles Times, Nation, July 3, 2011. http://articles.latimes.com/2011/jul/03/nation/la-na-clarence-thomas-20110703/2. Schacter, Daniel, Donna Addis, Demis Hassabis, Victoria Martin, R. Nathan Spreng, and Karl Szpunar. “The Future of Memory: Remembering, Imagining, and the Brain.” Neuron 76, no. 4 (November 21, 2012): 677–94. Schessler-Jandreau, Imke. “Fat America: A Historical Consideration of Diet and Weight Loss in the US.” 21st ICC 2008 (2009): 88–93.

War by Sebastian Junger

Demis Hassabis, Dunbar number, friendly fire, RAND corporation, satellite internet, Yom Kippur War

Crawford, MC, USN, and Capt. Ransom J. Arthur, MC, USN. “The Stress of Aircraft Carrier Landings.” Psychosomatic Medicine, Vol. 32, No. 6, November–December 1970. Milne, David. “Can People Really Be Scared to Death?” Psychiatric News, Vol. 37, No. 11, June 7, 2002. Mobbs, Dean, Predrag Petrovic, Jennifer L. Marchant, Demis Hassabis, Nikolaus Weiskopf, Ben Seymour, Raymond J. Dolan, and Christopher D. Frith. “When Fear Is Near: Threat Imminence Elicits Prefrontal-Periaqueductal Gray Shifts in Humans.” Science, Vol. 317, August 24, 2007. Moran, Lord. The Anatomy of Courage. Constable & Robinson Ltd., 1945. Morgan, Andrew.

Ten Lessons for a Post-Pandemic World by Fareed Zakaria

"there is no alternative" (TINA), 15-minute city, AlphaGo, An Inconvenient Truth, anti-fragile, Asian financial crisis, basic income, Bernie Sanders, Boris Johnson, butterfly effect, Capital in the Twenty-First Century by Thomas Piketty, car-free, carbon tax, central bank independence, clean water, cloud computing, colonial rule, contact tracing, coronavirus, COVID-19, Credit Default Swap, David Graeber, Day of the Dead, deep learning, DeepMind, deglobalization, Demis Hassabis, Deng Xiaoping, digital divide, Dominic Cummings, Donald Trump, Edward Glaeser, Edward Jenner, Elon Musk, Erik Brynjolfsson, failed state, financial engineering, Francis Fukuyama: the end of history, future of work, gentrification, George Floyd, gig economy, Gini coefficient, global pandemic, global reserve currency, global supply chain, green new deal, hiring and firing, housing crisis, imperial preference, income inequality, Indoor air pollution, invention of the wheel, Jane Jacobs, Jeff Bezos, Jeremy Corbyn, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Snow's cholera map, junk bonds, lockdown, Long Term Capital Management, low interest rates, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Martin Wolf, means of production, megacity, Mexican peso crisis / tequila crisis, middle-income trap, Monroe Doctrine, Nate Silver, Nick Bostrom, oil shock, open borders, out of africa, Parag Khanna, Paris climate accords, Peter Thiel, plutocrats, popular capitalism, Productivity paradox, purchasing power parity, remote working, reserve currency, reshoring, restrictive zoning, ride hailing / ride sharing, Ronald Reagan, secular stagnation, Silicon Valley, social distancing, software is eating the world, South China Sea, Steve Bannon, Steve Jobs, Steven Pinker, Suez crisis 1956, TED Talk, the built environment, The Death and Life of Great American Cities, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas L Friedman, Tim Cook: Apple, trade route, UNCLOS, universal basic income, urban planning, Washington Consensus, white flight, Works Progress Administration, zoonotic diseases

Norton, 1963), 358–73. 113 Jetson of the 1960s cartoon: “works three hours a day, three days a week,” per Sarah Ellison, “Reckitt Turns to Jetsons to Launch Detergent Gels,” Wall Street Journal, January 13, 2003; pushing a button, per Hanna-Barbera Wiki, “The Jetsons,” https://hanna-barbera.fandom.com/wiki/The_Jetsons. 113 four-day workweek: Zoe Didali, “As PM Finland’s Marin Could Renew Call for Shorter Work Week,” New Europe, January 2, 2020, https://www.neweurope.eu/article/finnish-pm-marin-calls-for-4-day-week-and-6-hours-working-day-in-the-country/. 114 “bullshit jobs”: David Graeber, Bullshit Jobs: A Theory (New York: Simon & Schuster, 2018). 115 “slaves of time without purpose”: McEwan, Machines Like Me. 116 atoms in the observable universe: David Silver and Demis Hassabis, “AlphaGo: Mastering the Ancient Game of Go with Machine Learning,” Google DeepMind, January 27, 2016, https://ai.googleblog.com/2016/01/alphago-mastering-ancient-game-of-go.html. 116 all fifty-seven games: Kyle Wiggers, “DeepMind’s Agent57 Beats Humans at 57 Classic Atari Games,” Venture Beat, March 31, 2020; Rebecca Jacobson, “Artificial Intelligence Program Teaches Itself to Play Atari Games—And It Can Beat Your High Score,” PBS NewsHour, February 20, 2015. 117 Stuart Russell: Stuart Russell, “3 Principles for Creating Safer AI,” TED2017, https://www.ted.com/talks/stuart_russell_3_principles_for_creating_safer_ai/transcript?

Scary Smart: The Future of Artificial Intelligence and How You Can Save Our World by Mo Gawdat

3D printing, accounting loophole / creative accounting, AI winter, AlphaGo, anthropic principle, artificial general intelligence, autonomous vehicles, basic income, Big Tech, Black Lives Matter, Black Monday: stock market crash in 1987, butterfly effect, call centre, carbon footprint, cloud computing, computer vision, coronavirus, COVID-19, CRISPR, cryptocurrency, deep learning, deepfake, DeepMind, Demis Hassabis, digital divide, digital map, Donald Trump, Elon Musk, fake news, fulfillment center, game design, George Floyd, global pandemic, Google Glasses, Google X / Alphabet X, Law of Accelerating Returns, lockdown, microplastics / micro fibres, Nick Bostrom, off-the-grid, OpenAI, optical character recognition, out of africa, pattern recognition, Ponzi scheme, Ray Kurzweil, recommendation engine, self-driving car, Silicon Valley, smart contracts, Stanislav Petrov, Stephen Hawking, subprime mortgage crisis, superintelligent machines, TED Talk, TikTok, Turing machine, Turing test, universal basic income, Watson beat the top human players on Jeopardy!, Y2K

That first time, unfortunately, I was shallow enough to ignore the universe sending me this message loud and clear. Instead, I focused, as most geeks would, on the coolness of what we were building. A couple of years or so before the yellow ball, Google had acquired DeepMind. Back then, the brilliant Demis Hassabis (CEO and founder of DeepMind) stood before the senior leadership group of Google to present to us the technology they had developed. This was the time when they taught AI to play Atari games. It’s not a huge stretch to spot the connection between the way machines learn and the way children do when the demo that is shown to you is of a machine playing a game.

The Upside of Irrationality: The Unexpected Benefits of Defying Logic at Work and at Home by Dan Ariely

Alvin Roth, An Inconvenient Truth, assortative mating, Bear Stearns, behavioural economics, Burning Man, business process, cognitive dissonance, Cornelius Vanderbilt, corporate governance, Daniel Kahneman / Amos Tversky, Demis Hassabis, end world poverty, endowment effect, Exxon Valdez, first-price auction, Ford Model T, Frederick Winslow Taylor, George Akerlof, happiness index / gross national happiness, hedonic treadmill, IKEA effect, Jean Tirole, job satisfaction, knowledge economy, knowledge worker, loss aversion, name-letter effect, Peter Singer: altruism, placebo effect, Richard Thaler, Saturday Night Live, search costs, second-price auction, Skinner box, software as a service, subprime mortgage crisis, sunk-cost fallacy, The Wealth of Nations by Adam Smith, ultimatum game, Upton Sinclair, young professional

Chu-Min Liao and Richard Masters, “Self-Focused Attention and Performance Failure under Psychological Stress,” Journal of Sport and Exercise Psychology 24, no. 3 (2002): 289–305. Kenneth McGraw, “The Detrimental Effects of Reward on Performance: A Literature Review and a Prediction Model,” in The Hidden Costs of Reward: New Perspectives on the Psychology of Human Motivation, ed. Mark Lepper and David Greene (New York: Erlbaum, 1978). Dean Mobbs, Demis Hassabis, Ben Seymour, Jennifer Marchant, Nikolaus Weiskopf, Raymond Dolan. and Christopher Frith, “Choking on the Money: Reward-Based Performance Decrements Are Associated with Midbrain Activity,” Psychological Science 20, no. 8 (2009): 955–962. Chapter 2: The Meaning of Labor: What Legos Can Teach Us about the Joy of Work Based on Dan Ariely, Emir Kamenica, and Dražen Prelec, “Man’s Search for Meaning: The Case of Legos,” Journal of Economic Behavior and Organization 67, nos. 3–4 (2008): 671–677.

AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee

"World Economic Forum" Davos, AI winter, Airbnb, Albert Einstein, algorithmic bias, algorithmic trading, Alignment Problem, AlphaGo, artificial general intelligence, autonomous vehicles, barriers to entry, basic income, bike sharing, business cycle, Cambridge Analytica, cloud computing, commoditize, computer vision, corporate social responsibility, cotton gin, creative destruction, crony capitalism, data science, deep learning, DeepMind, Demis Hassabis, Deng Xiaoping, deskilling, Didi Chuxing, Donald Trump, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, fake news, full employment, future of work, general purpose technology, Geoffrey Hinton, gig economy, Google Chrome, Hans Moravec, happiness index / gross national happiness, high-speed rail, if you build it, they will come, ImageNet competition, impact investing, income inequality, informal economy, Internet of things, invention of the telegraph, Jeff Bezos, job automation, John Markoff, Kickstarter, knowledge worker, Lean Startup, low skilled workers, Lyft, machine translation, mandatory minimum, Mark Zuckerberg, Menlo Park, minimum viable product, natural language processing, Neil Armstrong, new economy, Nick Bostrom, OpenAI, pattern recognition, pirate software, profit maximization, QR code, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, risk tolerance, Robert Mercer, Rodney Brooks, Rubik’s Cube, Sam Altman, Second Machine Age, self-driving car, sentiment analysis, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, SoftBank, Solyndra, special economic zone, speech recognition, Stephen Hawking, Steve Jobs, strong AI, TED Talk, The Future of Employment, Travis Kalanick, Uber and Lyft, uber lyft, universal basic income, urban planning, vertical integration, Vision Fund, warehouse robotics, Y Combinator

Kurzweil predicts that by 2029 we will have computers with intelligence comparable to that of humans (i.e., AGI), and that we will reach the singularity by 2045. Other utopian thinkers see AGI as something that will enable us to rapidly decode the mysteries of the physical universe. DeepMind founder Demis Hassabis predicts that the creation of superintelligence will allow human civilization to solve intractable problems, producing inconceivably brilliant solutions to global warming and previously incurable diseases. With superintelligent computers that understand the universe on levels that humans cannot even conceive of, these machines become not just tools for lightening the burdens of humanity; they approach the omniscience and omnipotence of a god.

Possible Minds: Twenty-Five Ways of Looking at AI by John Brockman

AI winter, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Alignment Problem, AlphaGo, artificial general intelligence, Asilomar, autonomous vehicles, basic income, Benoit Mandelbrot, Bill Joy: nanobots, Bletchley Park, Buckminster Fuller, cellular automata, Claude Shannon: information theory, Computing Machinery and Intelligence, CRISPR, Daniel Kahneman / Amos Tversky, Danny Hillis, data science, David Graeber, deep learning, DeepMind, Demis Hassabis, easy for humans, difficult for computers, Elon Musk, Eratosthenes, Ernest Rutherford, fake news, finite state, friendly AI, future of work, Geoffrey Hinton, Geoffrey West, Santa Fe Institute, gig economy, Hans Moravec, heat death of the universe, hype cycle, income inequality, industrial robot, information retrieval, invention of writing, it is difficult to get a man to understand something, when his salary depends on his not understanding it, James Watt: steam engine, Jeff Hawkins, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, Kickstarter, Laplace demon, Large Hadron Collider, Loebner Prize, machine translation, market fundamentalism, Marshall McLuhan, Menlo Park, military-industrial complex, mirror neurons, Nick Bostrom, Norbert Wiener, OpenAI, optical character recognition, paperclip maximiser, pattern recognition, personalized medicine, Picturephone, profit maximization, profit motive, public intellectual, quantum cryptography, RAND corporation, random walk, Ray Kurzweil, Recombinant DNA, Richard Feynman, Rodney Brooks, self-driving car, sexual politics, Silicon Valley, Skype, social graph, speech recognition, statistical model, Stephen Hawking, Steven Pinker, Stewart Brand, strong AI, superintelligent machines, supervolcano, synthetic biology, systems thinking, technological determinism, technological singularity, technoutopianism, TED Talk, telemarketer, telerobotics, The future is already here, the long tail, the scientific method, theory of mind, trolley problem, Turing machine, Turing test, universal basic income, Upton Sinclair, Von Neumann architecture, Whole Earth Catalog, Y2K, you are the product, zero-sum game

We tend to underestimate the complexity and creativity of the human brain and how amazingly general it is. If AI is to become more humanlike in its abilities, the machine-learning and neuroscience communities need to interact closely, something that is happening already. Some of today’s greatest exponents of machine learning—such as Geoffrey Hinton, Zoubin Ghahramani, and Demis Hassabis—have backgrounds in cognitive neuroscience, and their success has been at least in part due to attempts to model brainlike behavior in their algorithms. At the same time, neurobiology has also flourished. All sorts of tools have been developed to watch which neurons are firing and genetically manipulate them and see what’s happening in real time with inputs.

More From Less: The Surprising Story of How We Learned to Prosper Using Fewer Resources – and What Happens Next by Andrew McAfee

back-to-the-land, Bartolomé de las Casas, Berlin Wall, bitcoin, Blitzscaling, Branko Milanovic, British Empire, Buckminster Fuller, call centre, carbon credits, carbon footprint, carbon tax, Charles Babbage, clean tech, clean water, cloud computing, congestion pricing, Corn Laws, creative destruction, crony capitalism, data science, David Ricardo: comparative advantage, decarbonisation, DeepMind, degrowth, dematerialisation, Demis Hassabis, Deng Xiaoping, do well by doing good, Donald Trump, Edward Glaeser, en.wikipedia.org, energy transition, Erik Brynjolfsson, failed state, fake news, Fall of the Berlin Wall, Garrett Hardin, Great Leap Forward, Haber-Bosch Process, Hans Rosling, humanitarian revolution, hydraulic fracturing, income inequality, indoor plumbing, intangible asset, James Watt: steam engine, Jeff Bezos, job automation, John Snow's cholera map, joint-stock company, Joseph Schumpeter, Khan Academy, Landlord’s Game, Louis Pasteur, Lyft, Marc Andreessen, Marc Benioff, market fundamentalism, means of production, Michael Shellenberger, Mikhail Gorbachev, ocean acidification, oil shale / tar sands, opioid epidemic / opioid crisis, Paul Samuelson, peak oil, precision agriculture, price elasticity of demand, profit maximization, profit motive, risk tolerance, road to serfdom, Ronald Coase, Ronald Reagan, Salesforce, Scramble for Africa, Second Machine Age, Silicon Valley, Steve Jobs, Steven Pinker, Stewart Brand, Ted Nordhaus, TED Talk, telepresence, The Wealth of Nations by Adam Smith, Thomas Davenport, Thomas Malthus, Thorstein Veblen, total factor productivity, Tragedy of the Commons, Uber and Lyft, uber lyft, Veblen good, War on Poverty, We are as Gods, Whole Earth Catalog, World Values Survey

But thanks to digital tools, we’re learning quickly. In 2018, as part of a contest, the AlphaFold software developed by Google DeepMind correctly guessed the structure of twenty-five out of forty-three proteins it was shown; the second-place finisher guessed correctly three times. DeepMind cofounder Demis Hassabis says, “We [haven’t] solved the protein-folding problem, this is just a first step… but we have a good system and we have a ton of ideas we haven’t implemented yet.” As these good ideas accumulate, they might well let us make spider-strength materials. Energy. One of humanity’s most urgent tasks in the twenty-first century is to reduce greenhouse gas emissions.

I, Warbot: The Dawn of Artificially Intelligent Conflict by Kenneth Payne

Abraham Maslow, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, AlphaGo, anti-communist, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, Asperger Syndrome, augmented reality, Automated Insights, autonomous vehicles, backpropagation, Black Lives Matter, Bletchley Park, Boston Dynamics, classic study, combinatorial explosion, computer age, computer vision, Computing Machinery and Intelligence, coronavirus, COVID-19, CRISPR, cuban missile crisis, data science, deep learning, deepfake, DeepMind, delayed gratification, Demis Hassabis, disinformation, driverless car, drone strike, dual-use technology, Elon Musk, functional programming, Geoffrey Hinton, Google X / Alphabet X, Internet of things, job automation, John Nash: game theory, John von Neumann, Kickstarter, language acquisition, loss aversion, machine translation, military-industrial complex, move 37, mutually assured destruction, Nash equilibrium, natural language processing, Nick Bostrom, Norbert Wiener, nuclear taboo, nuclear winter, OpenAI, paperclip maximiser, pattern recognition, RAND corporation, ransomware, risk tolerance, Ronald Reagan, self-driving car, semantic web, side project, Silicon Valley, South China Sea, speech recognition, Stanislav Petrov, stem cell, Stephen Hawking, Steve Jobs, strong AI, Stuxnet, technological determinism, TED Talk, theory of mind, TikTok, Turing machine, Turing test, uranium enrichment, urban sprawl, V2 rocket, Von Neumann architecture, Wall-E, zero-sum game

The use of electronic games as a test-bed for reinforcement learning has been a particular research focus. The attraction to military minds is obvious—games are adversarial, and the goal is to win. The differences, however, are also profound, as we’ll see. 2015 saw the public arrival of DeepMind, a relative British newcomer to AI research, newly acquired by Google. DeepMind’s founder Demis Hassabis had trained in neuroscience, and he was explicit: DeepMind intended to create ‘general’ AI, with the attributes of human intelligence. Its first landmark breakthrough was an eighties throwback: classic Atari arcade games. The scoreboard in Space Invaders is an ideal motivator for reinforcement learning.

The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity by Amy Webb

"Friedman doctrine" OR "shareholder theory", Ada Lovelace, AI winter, air gap, Airbnb, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic bias, AlphaGo, Andy Rubin, artificial general intelligence, Asilomar, autonomous vehicles, backpropagation, Bayesian statistics, behavioural economics, Bernie Sanders, Big Tech, bioinformatics, Black Lives Matter, blockchain, Bretton Woods, business intelligence, Cambridge Analytica, Cass Sunstein, Charles Babbage, Claude Shannon: information theory, cloud computing, cognitive bias, complexity theory, computer vision, Computing Machinery and Intelligence, CRISPR, cross-border payments, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, Demis Hassabis, Deng Xiaoping, disinformation, distributed ledger, don't be evil, Donald Trump, Elon Musk, fail fast, fake news, Filter Bubble, Flynn Effect, Geoffrey Hinton, gig economy, Google Glasses, Grace Hopper, Gödel, Escher, Bach, Herman Kahn, high-speed rail, Inbox Zero, Internet of things, Jacques de Vaucanson, Jeff Bezos, Joan Didion, job automation, John von Neumann, knowledge worker, Lyft, machine translation, Mark Zuckerberg, Menlo Park, move fast and break things, Mustafa Suleyman, natural language processing, New Urbanism, Nick Bostrom, one-China policy, optical character recognition, packet switching, paperclip maximiser, pattern recognition, personalized medicine, RAND corporation, Ray Kurzweil, Recombinant DNA, ride hailing / ride sharing, Rodney Brooks, Rubik’s Cube, Salesforce, Sand Hill Road, Second Machine Age, self-driving car, seminal paper, SETI@home, side project, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart cities, South China Sea, sovereign wealth fund, speech recognition, Stephen Hawking, strong AI, superintelligent machines, surveillance capitalism, technological singularity, The Coming Technological Singularity, the long tail, theory of mind, Tim Cook: Apple, trade route, Turing machine, Turing test, uber lyft, Von Neumann architecture, Watson beat the top human players on Jeopardy!, zero day

The number of scientific papers on AI published by Chinese researchers more than doubled between 2010 and 2017.35 To be fair, papers and patents don’t necessarily mean that research will find its way into widespread use, but it was an early indication of how rattled Chinese leaders were at all the progress being made in the West—especially when it came to Go. By January 2014, Google had begun investing significantly in AI, which included more than $500 million to acquire a hot deep-learning startup called DeepMind and its three founders, neuroscientist Demis Hassabis, a former child prodigy in chess, machine-learning researcher Shane Legg, and entrepreneur Mustafa Suleyman. Part of the team’s appeal: they’d developed a program called AlphaGo. Within months, they were ready to test AlphaGo against a real human player. A match was arranged between DeepMind and Fan Hui, a Chinese-born professional Go player and one of the strongest professional masters in Europe.

The Road to Conscious Machines by Michael Wooldridge

Ada Lovelace, AI winter, algorithmic bias, AlphaGo, Andrew Wiles, Anthropocene, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, backpropagation, basic income, Bletchley Park, Boeing 747, British Empire, call centre, Charles Babbage, combinatorial explosion, computer vision, Computing Machinery and Intelligence, DARPA: Urban Challenge, deep learning, deepfake, DeepMind, Demis Hassabis, don't be evil, Donald Trump, driverless car, Elaine Herzberg, Elon Musk, Eratosthenes, factory automation, fake news, future of work, gamification, general purpose technology, Geoffrey Hinton, gig economy, Google Glasses, intangible asset, James Watt: steam engine, job automation, John von Neumann, Loebner Prize, Minecraft, Mustafa Suleyman, Nash equilibrium, Nick Bostrom, Norbert Wiener, NP-complete, P = NP, P vs NP, paperclip maximiser, pattern recognition, Philippa Foot, RAND corporation, Ray Kurzweil, Rodney Brooks, self-driving car, Silicon Valley, Stephen Hawking, Steven Pinker, strong AI, technological singularity, telemarketer, Tesla Model S, The Coming Technological Singularity, The Future of Employment, the scientific method, theory of mind, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, trolley problem, Turing machine, Turing test, universal basic income, Von Neumann architecture, warehouse robotics

For example, it turns out that road signs can be altered in such a way that, while a human has no difficulty interpreting them, they are completely misunderstood by the neural nets in a driverless car. Before we can use deep learning in sensitive applications, we need to understand these problems in much more detail. DeepMind The story of DeepMind, which I referred to earlier in this chapter, perfectly epitomizes the rise of deep learning. The company was founded in 2010 by Demis Hassabis, an AI researcher and computer games enthusiast, together with his school friend and entrepreneur Mustafa Suleyman, and they were joined by Shane Legg, a computational neuroscientist that Hassabis met while working at University College London. As we heard, Google acquired DeepMind early in 2014; I can recall seeing stories in the press about the acquisition, and starting in surprise when I saw that DeepMind were an AI company.

The AI Economy: Work, Wealth and Welfare in the Robot Age by Roger Bootle

"World Economic Forum" Davos, 3D printing, agricultural Revolution, AI winter, Albert Einstein, AlphaGo, Alvin Toffler, anti-work, antiwork, autonomous vehicles, basic income, Ben Bernanke: helicopter money, Bernie Sanders, Bletchley Park, blockchain, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Carl Icahn, Chris Urmson, computer age, Computing Machinery and Intelligence, conceptual framework, corporate governance, correlation does not imply causation, creative destruction, David Ricardo: comparative advantage, deep learning, DeepMind, deindustrialization, Demis Hassabis, deskilling, Dr. Strangelove, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, facts on the ground, fake news, financial intermediation, full employment, future of work, Future Shock, general purpose technology, Great Leap Forward, Hans Moravec, income inequality, income per capita, industrial robot, Internet of things, invention of the wheel, Isaac Newton, James Watt: steam engine, Jeff Bezos, Jeremy Corbyn, job automation, job satisfaction, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, Kevin Kelly, license plate recognition, low interest rates, machine translation, Marc Andreessen, Mark Zuckerberg, market bubble, mega-rich, natural language processing, Network effects, new economy, Nicholas Carr, Ocado, Paul Samuelson, Peter Thiel, Phillips curve, positional goods, quantitative easing, RAND corporation, Ray Kurzweil, Richard Florida, ride hailing / ride sharing, rising living standards, road to serfdom, Robert Gordon, Robert Shiller, Robert Solow, Rutger Bregman, Second Machine Age, secular stagnation, self-driving car, seminal paper, Silicon Valley, Silicon Valley billionaire, Simon Kuznets, Skype, social intelligence, spinning jenny, Stanislav Petrov, Stephen Hawking, Steven Pinker, synthetic biology, technological singularity, The Future of Employment, The Wealth of Nations by Adam Smith, Thomas Malthus, trade route, universal basic income, US Airways Flight 1549, Vernor Vinge, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, wealth creators, winner-take-all economy, world market for maybe five computers, Y2K, Yogi Berra

More importantly, we could see the widespread use of shared-use vehicles or electric vehicles, or both, without seeing a large-scale move to driverless vehicles. For, even without the ride sharing and the switch from petrol to electric, the widespread use of driverless cars is not as straightforward as is usually implied. Feasibility is not the issue. Safety is. Demis Hassabis, one of the founders of DeepMind, said in May 2018: “How do you ensure, mathematically, that systems are safe and will only do what we think they are going to do when they are out in the wild.”8 His misgivings are fully justified. Despite the claims of the manufacturers and developers of driverless vehicles that they are ultrasafe, a 2015 study from the University of Michigan discovered that the crash rate is higher for driverless vehicles.9 The study suggested that, when they occur, crashes are almost always not the fault of the driverless cars.

Them and Us: How Immigrants and Locals Can Thrive Together by Philippe Legrain

affirmative action, Albert Einstein, AlphaGo, autonomous vehicles, Berlin Wall, Black Lives Matter, Boris Johnson, Brexit referendum, British Empire, call centre, centre right, Chelsea Manning, clean tech, coronavirus, corporate social responsibility, COVID-19, creative destruction, crowdsourcing, data science, David Attenborough, DeepMind, Demis Hassabis, demographic dividend, digital divide, discovery of DNA, Donald Trump, double helix, Edward Glaeser, en.wikipedia.org, eurozone crisis, failed state, Fall of the Berlin Wall, future of work, illegal immigration, immigration reform, informal economy, Jane Jacobs, job automation, Jony Ive, labour market flexibility, lockdown, low cost airline, low interest rates, low skilled workers, lump of labour, Mahatma Gandhi, Mark Zuckerberg, Martin Wolf, Mary Meeker, mass immigration, moral hazard, Mustafa Suleyman, Network effects, new economy, offshore financial centre, open borders, open immigration, postnationalism / post nation state, purchasing power parity, remote working, Richard Florida, ride hailing / ride sharing, Rishi Sunak, Ronald Reagan, Silicon Valley, Skype, SoftBank, Steve Jobs, tech worker, The Death and Life of Great American Cities, The future is already here, The Future of Employment, Tim Cook: Apple, Tyler Cowen, urban sprawl, WeWork, Winter of Discontent, women in the workforce, working-age population

English physicist Francis Crick and American biologist James Watson concluded that it consisted of a three-dimensional double helix, based on the earlier discovery of DNA by a Swiss scientist, Friedrich Miescher, developed by Phoebus Levene, a Lithuanian-born American biochemist, and Erwin Chargaff, an Austro-Hungarian one.2 Or consider DeepMind, a London-based company doing groundbreaking practical research on artificial intelligence. Mustafa Suleyman, whose father was a Syrian-born taxi driver and mother an English nurse, met Demis Hassabis, whose father was Greek-Cypriot and mother Chinese Singaporean, when they were teenagers in north London. ‘Demis and I had conversations about how to impact the world, and he’d argue that we need to build these grand simulations that one day will model all the complex dynamics of our financial systems and solve our toughest social problems,’ Mustafa explains.

Exponential: How Accelerating Technology Is Leaving Us Behind and What to Do About It by Azeem Azhar

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 23andMe, 3D printing, A Declaration of the Independence of Cyberspace, Ada Lovelace, additive manufacturing, air traffic controllers' union, Airbnb, algorithmic management, algorithmic trading, Amazon Mechanical Turk, autonomous vehicles, basic income, Berlin Wall, Bernie Sanders, Big Tech, Bletchley Park, Blitzscaling, Boeing 737 MAX, book value, Boris Johnson, Bretton Woods, carbon footprint, Chris Urmson, Citizen Lab, Clayton Christensen, cloud computing, collective bargaining, computer age, computer vision, contact tracing, contact tracing app, coronavirus, COVID-19, creative destruction, crowdsourcing, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, data science, David Graeber, David Ricardo: comparative advantage, decarbonisation, deep learning, deglobalization, deindustrialization, dematerialisation, Demis Hassabis, Diane Coyle, digital map, digital rights, disinformation, Dissolution of the Soviet Union, Donald Trump, Double Irish / Dutch Sandwich, drone strike, Elon Musk, emotional labour, energy security, Fairchild Semiconductor, fake news, Fall of the Berlin Wall, Firefox, Frederick Winslow Taylor, fulfillment center, future of work, Garrett Hardin, gender pay gap, general purpose technology, Geoffrey Hinton, gig economy, global macro, global pandemic, global supply chain, global value chain, global village, GPT-3, Hans Moravec, happiness index / gross national happiness, hiring and firing, hockey-stick growth, ImageNet competition, income inequality, independent contractor, industrial robot, intangible asset, Jane Jacobs, Jeff Bezos, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Perry Barlow, Just-in-time delivery, Kickstarter, Kiva Systems, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, lockdown, low skilled workers, lump of labour, Lyft, manufacturing employment, Marc Benioff, Mark Zuckerberg, megacity, Mitch Kapor, Mustafa Suleyman, Network effects, new economy, NSO Group, Ocado, offshore financial centre, OpenAI, PalmPilot, Panopticon Jeremy Bentham, Peter Thiel, Planet Labs, price anchoring, RAND corporation, ransomware, Ray Kurzweil, remote working, RFC: Request For Comment, Richard Florida, ride hailing / ride sharing, Robert Bork, Ronald Coase, Ronald Reagan, Salesforce, Sam Altman, scientific management, Second Machine Age, self-driving car, Shoshana Zuboff, Silicon Valley, Social Responsibility of Business Is to Increase Its Profits, software as a service, Steve Ballmer, Steve Jobs, Stuxnet, subscription business, synthetic biology, tacit knowledge, TaskRabbit, tech worker, The Death and Life of Great American Cities, The Future of Employment, The Nature of the Firm, Thomas Malthus, TikTok, Tragedy of the Commons, Turing machine, Uber and Lyft, Uber for X, uber lyft, universal basic income, uranium enrichment, vertical integration, warehouse automation, winner-take-all economy, workplace surveillance , Yom Kippur War

Further thanks to the many teachers who helped me understand the world of computing, politics and economics, including John Wilcox, Stephen Bishop, Nick Lord, Ray Bradley, Mike Clugston, Don Markwell, Vijay Joshi, the late John Lucas, the late David Bostock and the late Jack Schofield. Many thanks to the dozens of guests on my podcast whose ideas have helped enrich my thesis, including Laetitia Vitaud, Bill Janeway, Carissa Véliz, Tony Blair, Demis Hassabis, Sam Altman, Philip Auerswald, Scott Santens, Jeff Sachs, Andrew Yang, Jack Clark, Trent McConaghy, Michael Liebreich, Casper Klynge, Kate Raworth, Sir Richard Barrons, Joanna Bryson, Stuart Russell, Cory Doctorow, Kai-Fu Lee, Matt Clifford, Marietje Schaake, Yuval Noah Harari, Mariana Mazzucato, Mike Zelkind, Josh Hoffman, Binyamin Applebaum, Kate Crawford, Matt Ocko, Jeremy O’Brien, Sam Altman, Audrey Tang, Vijay Pande, Matt Clifford, Fei-Fei Li, Adena Friedman, Kersti Kaljulaid, Astro Teller, Deep Nishar, Cesar Hidalgo, Ian Bremmer, Brad Smith, Nicole Eagan, Meredith Whittaker, Gary Marcus, Andrew Ng, Shoshana Zuboff, Jürgen Schmidhuber, Gina Neff, Missy Cummings, Eric Topol, Cathie Wood, Michael Liebreich, Mariarosaria Taddeo and Ronit Ghose.

Machine, Platform, Crowd: Harnessing Our Digital Future by Andrew McAfee, Erik Brynjolfsson

"World Economic Forum" Davos, 3D printing, additive manufacturing, AI winter, Airbnb, airline deregulation, airport security, Albert Einstein, algorithmic bias, AlphaGo, Amazon Mechanical Turk, Amazon Web Services, Andy Rubin, AOL-Time Warner, artificial general intelligence, asset light, augmented reality, autism spectrum disorder, autonomous vehicles, backpropagation, backtesting, barriers to entry, behavioural economics, bitcoin, blockchain, blood diamond, British Empire, business cycle, business process, carbon footprint, Cass Sunstein, centralized clearinghouse, Chris Urmson, cloud computing, cognitive bias, commoditize, complexity theory, computer age, creative destruction, CRISPR, crony capitalism, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, data science, Dean Kamen, deep learning, DeepMind, Demis Hassabis, discovery of DNA, disintermediation, disruptive innovation, distributed ledger, double helix, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ethereum, ethereum blockchain, everywhere but in the productivity statistics, Evgeny Morozov, fake news, family office, fiat currency, financial innovation, general purpose technology, Geoffrey Hinton, George Akerlof, global supply chain, Great Leap Forward, Gregor Mendel, Hernando de Soto, hive mind, independent contractor, information asymmetry, Internet of things, inventory management, iterative process, Jean Tirole, Jeff Bezos, Jim Simons, jimmy wales, John Markoff, joint-stock company, Joseph Schumpeter, Kickstarter, Kiva Systems, law of one price, longitudinal study, low interest rates, Lyft, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Marc Andreessen, Marc Benioff, Mark Zuckerberg, meta-analysis, Mitch Kapor, moral hazard, multi-sided market, Mustafa Suleyman, Myron Scholes, natural language processing, Network effects, new economy, Norbert Wiener, Oculus Rift, PageRank, pattern recognition, peer-to-peer lending, performance metric, plutocrats, precision agriculture, prediction markets, pre–internet, price stability, principal–agent problem, Project Xanadu, radical decentralization, Ray Kurzweil, Renaissance Technologies, Richard Stallman, ride hailing / ride sharing, risk tolerance, Robert Solow, Ronald Coase, Salesforce, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, slashdot, smart contracts, Snapchat, speech recognition, statistical model, Steve Ballmer, Steve Jobs, Steven Pinker, supply-chain management, synthetic biology, tacit knowledge, TaskRabbit, Ted Nelson, TED Talk, the Cathedral and the Bazaar, The Market for Lemons, The Nature of the Firm, the strength of weak ties, Thomas Davenport, Thomas L Friedman, too big to fail, transaction costs, transportation-network company, traveling salesman, Travis Kalanick, Two Sigma, two-sided market, Tyler Cowen, Uber and Lyft, Uber for X, uber lyft, ubercab, Vitalik Buterin, warehouse robotics, Watson beat the top human players on Jeopardy!, winner-take-all economy, yield management, zero day

So we made appointments in Cambridge, New York, London, San Francisco, Silicon Valley, Washington, DC, and other places, and set out. In addition to the interviewees who are quoted in this book, many others taught us a lot: Daron Acemoglu Susan Athey David Autor Jeff Bezos Nick Bloom Christian Catalini Michael Chui Paul Daugherty Tom Davenport Tom Friedman Demis Hassabis Reid Hoffman Jeremy Howard Dean Kamen Andy Karsner Christine Lagarde Yann LeCun Shane Legg John Leonard David Lipton Tom Malone James Manyika Kristina McElheren Tom Mitchell Elon Musk Ramez Naam Tim O’Reilly Gill Pratt Francesa Rossi Daniela Rus Stuart Russell Eric Schmidt Mustafa Suleyman Max Tegmark Sebastian Thrun But you can put off writing for only so long.

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

23andMe, Aaron Swartz, agricultural Revolution, algorithmic trading, Anne Wojcicki, Anthropocene, anti-communist, Anton Chekhov, autonomous vehicles, behavioural economics, Berlin Wall, call centre, Chekhov's gun, Chris Urmson, cognitive dissonance, Columbian Exchange, computer age, DeepMind, Demis Hassabis, Deng Xiaoping, don't be evil, driverless car, 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, Great Leap Forward, Intergovernmental Panel on Climate Change (IPCC), invention of writing, invisible hand, Isaac Newton, job automation, John Markoff, Kevin Kelly, lifelogging, low interest rates, means of production, Mikhail Gorbachev, Minecraft, Moneyball by Michael Lewis explains big data, Monkeys Reject Unequal Pay, mutually assured destruction, new economy, Nick Bostrom, pattern recognition, peak-end rule, Peter Thiel, placebo effect, Ray Kurzweil, self-driving car, Silicon Valley, Silicon Valley ideology, stem cell, Steven Pinker, telemarketer, The future is already here, 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

Deep Blue was given a head start by its creators, who preprogrammed it not only with the basic rules of chess, but also with detailed instructions regarding chess strategies. A new generation of AI uses machine learning to do even more remarkable and elegant things. In February 2015 a program developed by Google DeepMind learned by itself how to play forty-nine classic Atari games. One of the developers, Dr Demis Hassabis, explained that ‘the only information we gave the system was the raw pixels on the screen and the idea that it had to get a high score. And everything else it had to figure out by itself.’ The program managed to learn the rules of all the games it was presented with, from Pac-Man and Space Invaders to car racing and tennis games.

Coders: The Making of a New Tribe and the Remaking of the World by Clive Thompson

"Margaret Hamilton" Apollo, "Susan Fowler" uber, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 4chan, 8-hour work day, Aaron Swartz, Ada Lovelace, AI winter, air gap, Airbnb, algorithmic bias, AlphaGo, Amazon Web Services, Andy Rubin, Asperger Syndrome, augmented reality, Ayatollah Khomeini, backpropagation, barriers to entry, basic income, behavioural economics, Bernie Sanders, Big Tech, bitcoin, Bletchley Park, blockchain, blue-collar work, Brewster Kahle, Brian Krebs, Broken windows theory, call centre, Cambridge Analytica, cellular automata, Charles Babbage, Chelsea Manning, Citizen Lab, clean water, cloud computing, cognitive dissonance, computer vision, Conway's Game of Life, crisis actor, crowdsourcing, cryptocurrency, Danny Hillis, data science, David Heinemeier Hansson, deep learning, DeepMind, Demis Hassabis, disinformation, don't be evil, don't repeat yourself, Donald Trump, driverless car, dumpster diving, Edward Snowden, Elon Musk, Erik Brynjolfsson, Ernest Rutherford, Ethereum, ethereum blockchain, fake news, false flag, Firefox, Frederick Winslow Taylor, Free Software Foundation, Gabriella Coleman, game design, Geoffrey Hinton, glass ceiling, Golden Gate Park, Google Hangouts, Google X / Alphabet X, Grace Hopper, growth hacking, Guido van Rossum, Hacker Ethic, hockey-stick growth, HyperCard, Ian Bogost, illegal immigration, ImageNet competition, information security, Internet Archive, Internet of things, Jane Jacobs, John Markoff, Jony Ive, Julian Assange, Ken Thompson, Kickstarter, Larry Wall, lone genius, Lyft, Marc Andreessen, Mark Shuttleworth, Mark Zuckerberg, Max Levchin, Menlo Park, meritocracy, microdosing, microservices, Minecraft, move 37, move fast and break things, Nate Silver, Network effects, neurotypical, Nicholas Carr, Nick Bostrom, no silver bullet, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, Oculus Rift, off-the-grid, OpenAI, operational security, opioid epidemic / opioid crisis, PageRank, PalmPilot, paperclip maximiser, pattern recognition, Paul Graham, paypal mafia, Peter Thiel, pink-collar, planetary scale, profit motive, ransomware, recommendation engine, Richard Stallman, ride hailing / ride sharing, Rubik’s Cube, Ruby on Rails, Sam Altman, Satoshi Nakamoto, Saturday Night Live, scientific management, self-driving car, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, single-payer health, Skype, smart contracts, Snapchat, social software, software is eating the world, sorting algorithm, South of Market, San Francisco, speech recognition, Steve Wozniak, Steven Levy, systems thinking, TaskRabbit, tech worker, techlash, TED Talk, the High Line, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, universal basic income, urban planning, Wall-E, Watson beat the top human players on Jeopardy!, WeWork, WikiLeaks, women in the workforce, Y Combinator, Zimmermann PGP, éminence grise

Use Google,” Washington Post, March 14, 2016, accessed August 19, 2018, https://www.washingtonpost.com/national/health-science/how-you-beat-one-of-the-best-go-players-in-the-world-use-google/2016/03/14/1efd1176-e6fc-11e5-b0fd-073d5930a7b7_story.html. atoms in the universe: Alan Levinovitz, “The Mystery of Go, the Ancient Game That Computers Still Can’t Win,” Wired, May 12, 2014, accessed August 19, 2018, https://www.wired.com/2014/05/the-world-of-computer-go; David Silver and Demis Hassabis, “AlphaGo: Mastering the Ancient Game of Go with Machine Learning,” Google AI Blog, January 27, 2016, accessed August 19, 2018, https://ai.googleblog.com/2016/01/alphago-mastering-ancient-game-of-go.html. model of the game: Silver and Hassabis, “AlphaGo.” tales about AlphaGo: Cade Metz, “The Sadness and Beauty of Watching Google’s AI Play Go,” Wired, March 11, 2016, accessed August 19, 2018, https://www.wired.com/2016/03/sadness-beauty-watching-googles-ai-play-go.

Superintelligence: Paths, Dangers, Strategies by Nick Bostrom

agricultural Revolution, AI winter, Albert Einstein, algorithmic trading, anthropic principle, Anthropocene, anti-communist, artificial general intelligence, autism spectrum disorder, autonomous vehicles, backpropagation, barriers to entry, Bayesian statistics, bioinformatics, brain emulation, cloud computing, combinatorial explosion, computer vision, Computing Machinery and Intelligence, cosmological constant, dark matter, DARPA: Urban Challenge, data acquisition, delayed gratification, Demis Hassabis, demographic transition, different worldview, Donald Knuth, Douglas Hofstadter, driverless car, Drosophila, Elon Musk, en.wikipedia.org, endogenous growth, epigenetics, fear of failure, Flash crash, Flynn Effect, friendly AI, general purpose technology, Geoffrey Hinton, Gödel, Escher, Bach, hallucination problem, Hans Moravec, income inequality, industrial robot, informal economy, information retrieval, interchangeable parts, iterative process, job automation, John Markoff, John von Neumann, knowledge worker, Large Hadron Collider, longitudinal study, machine translation, megaproject, Menlo Park, meta-analysis, mutually assured destruction, Nash equilibrium, Netflix Prize, new economy, Nick Bostrom, Norbert Wiener, NP-complete, nuclear winter, operational security, optical character recognition, paperclip maximiser, pattern recognition, performance metric, phenotype, prediction markets, price stability, principal–agent problem, race to the bottom, random walk, Ray Kurzweil, recommendation engine, reversible computing, search costs, social graph, speech recognition, Stanislav Petrov, statistical model, stem cell, Stephen Hawking, Strategic Defense Initiative, strong AI, superintelligent machines, supervolcano, synthetic biology, technological singularity, technoutopianism, The Coming Technological Singularity, The Nature of the Firm, Thomas Kuhn: the structure of scientific revolutions, time dilation, Tragedy of the Commons, transaction costs, trolley problem, Turing machine, Vernor Vinge, WarGames: Global Thermonuclear War, Watson beat the top human players on Jeopardy!, World Values Survey, zero-sum game

For extensive discussions that have helped clarify my thinking I am grateful to a large set of people, including Ross Andersen, Stuart Armstrong, Owen Cotton-Barratt, Nick Beckstead, David Chalmers, Paul Christiano, Milan Ćirković, Daniel Dennett, David Deutsch, Daniel Dewey, Eric Drexler, Peter Eckersley, Amnon Eden, Owain Evans, Benja Fallenstein, Alex Flint, Carl Frey, Ian Goldin, Katja Grace, J. Storrs Hall, Robin Hanson, Demis Hassabis, James Hughes, Marcus Hutter, Garry Kasparov, Marcin Kulczycki, Shane Legg, Moshe Looks, Willam MacAskill, Eric Mandelbaum, James Martin, Lillian Martin, Roko Mijic, Vincent Mueller, Elon Musk, Seán Ó hÉigeartaigh, Toby Ord, Dennis Pamlin, Derek Parfit, David Pearce, Huw Price, Martin Rees, Bill Roscoe, Stuart Russell, Anna Salamon, Lou Salkind, Anders Sandberg, Julian Savulescu, Jürgen Schmidhuber, Nicholas Shackel, Murray Shanahan, Noel Sharkey, Carl Shulman, Peter Singer, Dan Stoicescu, Jaan Tallinn, Alexander Tamas, Max Tegmark, Roman Yampolskiy, and Eliezer Yudkowsky.

Four Battlegrounds by Paul Scharre

2021 United States Capitol attack, 3D printing, active measures, activist lawyer, AI winter, AlphaGo, amateurs talk tactics, professionals talk logistics, artificial general intelligence, ASML, augmented reality, Automated Insights, autonomous vehicles, barriers to entry, Berlin Wall, Big Tech, bitcoin, Black Lives Matter, Boeing 737 MAX, Boris Johnson, Brexit referendum, business continuity plan, business process, carbon footprint, chief data officer, Citizen Lab, clean water, cloud computing, commoditize, computer vision, coronavirus, COVID-19, crisis actor, crowdsourcing, DALL-E, data is not the new oil, data is the new oil, data science, deep learning, deepfake, DeepMind, Demis Hassabis, Deng Xiaoping, digital map, digital rights, disinformation, Donald Trump, drone strike, dual-use technology, Elon Musk, en.wikipedia.org, endowment effect, fake news, Francis Fukuyama: the end of history, future of journalism, future of work, game design, general purpose technology, Geoffrey Hinton, geopolitical risk, George Floyd, global supply chain, GPT-3, Great Leap Forward, hive mind, hustle culture, ImageNet competition, immigration reform, income per capita, interchangeable parts, Internet Archive, Internet of things, iterative process, Jeff Bezos, job automation, Kevin Kelly, Kevin Roose, large language model, lockdown, Mark Zuckerberg, military-industrial complex, move fast and break things, Nate Silver, natural language processing, new economy, Nick Bostrom, one-China policy, Open Library, OpenAI, PalmPilot, Parler "social media", pattern recognition, phenotype, post-truth, purchasing power parity, QAnon, QR code, race to the bottom, RAND corporation, recommendation engine, reshoring, ride hailing / ride sharing, robotic process automation, Rodney Brooks, Rubik’s Cube, self-driving car, Shoshana Zuboff, side project, Silicon Valley, slashdot, smart cities, smart meter, Snapchat, social software, sorting algorithm, South China Sea, sparse data, speech recognition, Steve Bannon, Steven Levy, Stuxnet, supply-chain attack, surveillance capitalism, systems thinking, tech worker, techlash, telemarketer, The Brussels Effect, The Signal and the Noise by Nate Silver, TikTok, trade route, TSMC

., https://cloud.google.com/tpu; “Cloud Tensor Processing Units (TPUs),” Google Cloud, n.d., https://cloud.google.com/tpu/docs/tpus. 298reduced energy consumption: The metric DeepMind used to compare AlphaGo versions, thermal design power (TDP), is not a direct measure of energy consumption. It is a rough first-order proxy, however, for power consumption. David Silver and Demis Hassabis, “AlphaGo Zero: Starting From Scratch,” DeepMind Blog, October 18, 2017, https://deepmind.com/blog/article/alphago-zero-starting-scratch. 298reduced compute usage to only 4 TPUs: Silver and Hassabis, “AlphaGo Zero: Starting From Scratch”; “AlphaGo,” DeepMind, n.d., https://deepmind.com/research/case-studies/alphago-the-story-so-far; David Silver et al., “Mastering the Game of Go without Human Knowledge,” Nature 550 (October 19 2017), 354–355, https://www.nature.com/articles/nature24270.epdf. 298reduced the compute needed for training by a factor of eight: Hernandez and Brown, Measuring the Algorithmic Efficiency of Neural Networks, 18. 298may make AI models available: Desislavov et al., Compute and Energy Consumption Trends in Deep Learning Inference; Sharir et al., The Cost of Training NLP Models, 3. 298AI training costs could be as much as thirty times higher: Khan and Mann, AI Chips, 26. 299costly and locks out university researchers: Rodney Brooks, “A Better Lesson,” Rodney Brooks (personal website), March 19, 2019, https://rodneybrooks.com/a-better-lesson/; Kevin Vu, “Compute Goes Brrr: Revisiting Sutton’s Bitter Lesson for Artificial Intelligence,” DZone.com, March 11, 2021, https://dzone.com/articles/compute-goes-brrr-revisiting-suttons-bitter-lesson; Bommasani et al., On the Opportunities and Risks of Foundation Models. 299contributes to carbon emissions: “On the Dangers of Stochastic Parrots”; Brooks, “A Better Lesson”; Vu, “Compute Goes Brrr”; Lasse F.

The Irrational Bundle by Dan Ariely

accounting loophole / creative accounting, air freight, Albert Einstein, Alvin Roth, An Inconvenient Truth, assortative mating, banking crisis, Bear Stearns, behavioural economics, Bernie Madoff, Black Swan, Broken windows theory, Burning Man, business process, cashless society, Cass Sunstein, clean water, cognitive dissonance, cognitive load, compensation consultant, computer vision, Cornelius Vanderbilt, corporate governance, credit crunch, Credit Default Swap, Daniel Kahneman / Amos Tversky, delayed gratification, Demis Hassabis, Donald Trump, end world poverty, endowment effect, Exxon Valdez, fake it until you make it, financial engineering, first-price auction, Ford Model T, Frederick Winslow Taylor, fudge factor, Garrett Hardin, George Akerlof, Gordon Gekko, greed is good, happiness index / gross national happiness, hedonic treadmill, IKEA effect, Jean Tirole, job satisfaction, John Perry Barlow, Kenneth Arrow, knowledge economy, knowledge worker, lake wobegon effect, late fees, loss aversion, Murray Gell-Mann, name-letter effect, new economy, operational security, Pepsi Challenge, Peter Singer: altruism, placebo effect, price anchoring, Richard Feynman, Richard Thaler, Saturday Night Live, Schrödinger's Cat, search costs, second-price auction, Shai Danziger, shareholder value, Silicon Valley, Skinner box, Skype, social contagion, software as a service, Steve Jobs, subprime mortgage crisis, sunk-cost fallacy, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Tragedy of the Commons, ultimatum game, Upton Sinclair, Walter Mischel, young professional

Chu-Min Liao and Richard Masters, “Self-Focused Attention and Performance Failure under Psychological Stress,” Journal of Sport and Exercise Psychology 24, no. 3 (2002): 289–305. Kenneth McGraw, “The Detrimental Effects of Reward on Performance: A Literature Review and a Prediction Model,” in The Hidden Costs of Reward: New Perspectives on the Psychology of Human Motivation, ed. Mark Lepper and David Greene (New York: Erlbaum, 1978). Dean Mobbs, Demis Hassabis, Ben Seymour, Jennifer Marchant, Nikolaus Weiskopf, Raymond Dolan. and Christopher Frith, “Choking on the Money: Reward-Based Performance Decrements Are Associated with Midbrain Activity,” Psychological Science 20, no. 8 (2009): 955–962. Chapter 2: The Meaning of Labor: What Legos Can Teach Us about the Joy of Work Based on Dan Ariely, Emir Kamenica, and Dražen Prelec, “Man’s Search for Meaning: The Case of Legos,” Journal of Economic Behavior and Organization 67, nos. 3–4 (2008): 671–677.