The five best books to understand AI

IN RECENT years artificial intelligence (AI) has undergone a revolution. After decades of modest progress that never quite lived up to its promise, a different approach—relying on big data and stats, not clever algorithms—made huge strides in solving real-world problems like voice- and image-recognition and self-driving cars. Also in the past ten years, a lot of books have been published that aim to explain what AI is, where it’s going and why it matters. Books by AI academics do well at explaining the technology but are less robust at foreseeing the implications. For that, bright lights from outside the AI world do better. Five books in particular stand out.

Novacene: The Coming Age of Hyperintelligence. By James Lovelock with Bryan Appleyard. The MIT Press; 160 pages; $22.95. Allen Lane; £14.99

In a slim volume, James Lovelock—a British scientist who originated the Gaia hypothesis that the Earth acts as a self-regulating, living organism—predicts how “cyborgs” may help people in the future, notably by keeping the planet temperate so both man and machine can survive. The AI-infused bots will be vastly more intelligent and faster-thinking than humans (and may keep us as pets, he suggests). But we should be willing to cede our place on the pedestal to a superior intelligence, he says, even if their answers are so intricately reasoned that they are ineffable to the human mind. Mr Lovelock passed away last month on his 103rd birthday, so the book represents some of the final thoughts of a very special thinker (read our review).

The Age of AI. By Henry Kissinger, Eric Schmidt and Daniel Huttenlocher. Little, Brown and Company; 272 pages; $30. John Murray; £20

The crux of this book is a big idea: AI marks “a new epoch” since it ends the Enlightenment’s ethos that placed humans at the centre of all that is knowable (displacing God), putting in their stead machines with superior intelligence. The book does a great job of explaining how AI systems work, though a chapter on business is lacklustre. Yet the analysis on international security is exceptional. Henry Kissinger, America’s pre-eminent foreign-policy thinker, is clearly spooked by AI weapons and calls on the West to develop them (so as to not cede them to a foe) while urging immediate AI arms-control talks. Since AI responses may be unlike human ones, the environment is more unpredictable and dangerous, the book argues (read our review).

AI Superpowers: China, Silicon Valley and the New World Order. By Kai-Fu Lee. Houghton Mifflin Harcourt; 272 pages; $28

Born in Taiwan, the author studied AI in America, became an executive at Apple, Microsoft and Google and now runs a venture-capital fund in China—so is well placed to evaluate the two countries’ rivalry. American AI dominance will give way to China, he believes, because the Chinese work harder and have more data (in part because of looser standards on privacy). The liberal belief that openness is required for innovation is being proved false, he claims. Yet a neocolonial situation is forming whereby all countries will need to align with an AI ecosystem from China or America for everything from health-care systems to corporate IT and military equipment. Mr Lee’s prognostications are fascinating, regardless of whether they are borne out (read our review).

Prediction Machines. By Ajay Agrawal, Joshua Gans and Avi Goldfarb. Harvard Business Review; 272 pages; $30

Three economists at the University of Toronto wisely frame AI as lowering the cost of making predictions, in the same way as computers lowered the cost of doing maths. When doing so is exponentially less expensive, society finds ways to transform problems into ones the technology can handle. Hence books, photos, video and music became domains for computers to handle, displacing physical formats. Likewise, AI will replace humans, from self-driving cars to office automation. But all is not lost: as the cost of predictions go down, the value of human judgement will increase, the authors argue. (Read our economics column on their recent work).

Possible Minds: Twenty-Five Ways of Looking at AI. Edited by John Brockman. Penguin Press; 320 pages; $28

This compilation of essays from an all-star cast of experts from across scientific fields draws together smart thinking about the technology. Judea Pearl, who brought causal reasoning into statistics, explains AI’s blind spot from number-crunching alone. Stuart Russell, a computer scientist, synthesises his work on developing “provably” beneficial AI to ensure the machines don’t go rogue. Other essays by thinkers such as Steven Pinker and Alison Gopnik look at human cognition compared to AI’s answers, and how humans can stay relevant. The essays are a tasting menu of intriguing ideas and a good introduction to the topic.

These books provide an optimistic look at data and AI, yet there is a budding genre of negative takes. They, too, are good—if read with a critical eye. The best is Privacy is Power by Carissa Véliz on the need to take control of personal information (read our blurb). Weapons of Math Destruction by Cathy O’Neil is an unfair hit-job: the data are innocent—it’s people who are to blame! (Listen to our podcast with the author.) The Atlas of AI by Kate Crawford is a litany of AI’s woes, from its environmental toll to unemployment.

To pick just one book, it would be Mr Kissinger’s, et al. Artificial intelligence humbles humanity and their analysis shrewdly explains why. ■

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Our deputy executive editor is the co-author of a book on AI and human decision-making:

Framers: Make Better Decisions in the Age of Big Data. By Kenneth Cukier, Viktor Mayer-Schönberger and Francis de Véricourt. Dutton; 272 pages; $28. WH Allen; £20

An exploration of what people can do that AI can’t: use mental models to see the world in a new way. “Different, and better, than the usual recipes for smart thinking”, said the Financial Times.
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