The tech industry loves trying to convince us that this next thing is going to be the real deal, transforming society and generating billions in the process. Sometimes, as with personal computers, the internet, smartphones and social media, the hype is justified; other times — remember NFTs? the Metaverse? — not so much. It’s easy to get lost in the daily froth of gadgets and gimmicks, booms and busts, winners and losers.

Take ChatGPT, for instance. It swept the world, setting the record for fastest-growing app in history and spawning countless clones. But less than a year after its initial release, cracks are surfacing: The cost of running a chatbot has become a serious issue. The tendency of chatbots to confidently spew out falsehoods doesn’t look to be going away anytime soon. And Microsoft’s plan to reinvent web search with chatbots hasn’t even dented Google’s market dominance.

Are chatbots ushering in a new era of civilization, or are they yet another overhyped, passing fad? It’s too early to tell. But when we zoom out a bit and look past the daily ebbs and flows, it’s easier to see the larger currents of technological change. Chatbots are just one application of large language models, which themselves are just one corner of contemporary AI. And AI is a prominent part of a massive technological wave that we are just beginning to experience.

This “Coming Wave” is the subject — and the title — of a sweeping, thought-provoking new book by Mustafa Suleyman (writing with Michael Bhaskar), a co-founder of the prominent AI lab DeepMind, which was acquired by Google in 2014.

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I like to think of AI as data science 3.0. Traditional statistics, from means and medians to p-values and tests for significance, revolutionized science, medicine, and many aspects of government and business operations, particularly from the 19th century onward. The early 2000s heralded a second period, one more heavily reliant on computers to process large data sets (“big data”). Higher-resolution statistics became the engine of such things as tech giants’ predictions about what consumers are most likely to buy next and political campaigns such as Barack Obama’s 2008 election team, which decided how to focus its efforts using unprecedently fine-grained voter information.

In the current, third wave of data science, the emphasis is moving from making predictions to automatically acting upon them, and from analyzing data to generating it. Whatever big changes to society occur in the coming decades will probably be related to data in some way. And whatever new techniques underlie those changes will probably be labeled AI — no matter how distant they may be from what we call AI today.

Suleyman does not describe AI as I have here, but he does similarly see it as part of a larger technological era, one that is of a piece with genetic engineering, especially gene editing and synthetic biology. Also caught up in the currents are other potentially game-changing technologies such as quantum computing and fusion power. Suleyman convincingly argues that none of these technologies develops in isolation; they proceed synergistically, as progress in one area spurs progress in the others.

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Suleyman sees a striking commonality in the technologies making up his coming wave: They proliferate power, and they do this by reducing the costs of acting upon information. This, in his view, distinguishes it from the previous wave of internet-related technologies that reduced the costs of broadcasting information. While the world is too messy to fit neatly into simple summations of this kind, I find Suleyman’s framing quite reasonable and helpful: Look less at the individual technologies within a wave, he suggests, and more at what these technologies enable people to do.

Suleyman makes a compelling case that tremendous progress for humanity is possible with what’s coming, but he also argues that this wave will flood us with devastation if we don’t work harder to direct it. Whether deliberate weaponization of powerful tools or accidental mishaps of unprecedented scale, there is a lot that could go very wrong.

While fanciful doomsday prophesying is a popular preoccupation in some tech and tech-adjacent circles, this book provides a nicely grounded analysis. Rather than the familiar list of Hollywood robot takeovers (HAL and Skynet begone!), you’ll find levelheaded discussions emphasizing the sociopolitical and socioeconomic context in which technology develops and exists.

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Suleyman also diverges from the tech industry’s most common line in the ways he impressively draws from the past to help us understand the present and prepare for the future. Historical vignettes on technological progress, from the Industrial Revolution to the combustion engine to the early days of the internet, are engagingly woven throughout the book. As these examples demonstrate, technological waves are nearly unstoppable — and we shouldn’t want to stop them anyway, because technological stagnation is not the answer. As he astutely writes, “Modern civilization writes checks only continual technological development can cash.”

It is particularly impressive — and welcome — that Suleyman includes a wide-ranging and thoughtful discussion on concrete, practical steps we can take. His suggestions are remarkably broad and balanced. He forcefully rejects the hyper-libertarianism of tech moguls such as Peter Thiel, and argues for strong regulation and international cooperation, but he recognizes the myopic nature of modern governments and the myriad ways regulation fails. On economic questions, he doesn’t go as far as some scathing critiques of the capitalistic underpinnings of AI, but he goes much further than most in the tech industry when he discusses the role of financial incentives in encouraging dangerous risk-taking. He also offers some intriguing ideas about tax policy and corporate restructuring that deserve more attention.

Suleyman falls into some traps common to tech leaders, such as taking exponential progress as a given when it isn’t, underplaying the human cost of building AI systems and highlighting his own efforts to raise the alarm over AI while conspicuously omitting mention of the many other individuals who have been doing so for years. It is particularly egregious that not a single one of the women profiled in this recent Rolling Stone story is mentioned, or cited, in Suleyman’s book. And he takes a questionable stance on open-source software, suggesting that AI systems shouldn’t be distributed widely, even though many experts believe this is the best way to uncover their problems so we can try to fix them. But these issues don’t detract much from the book’s overall value and importance.

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Whether ChatGPT ends up being central to the coming wave or merely debris washed ashore by the technologies that really matter remains to be seen. Instead of focusing on which apps will stand the test of time and which start-ups will succeed, we should look up and recognize what is fast approaching, and that there are many things we can do to prepare for it. Suleyman provides a much-needed — and unusually thoughtful, expansive, historically rooted and engagingly written — guide.

Noah Giansiracusa is a professor of mathematics and data science at Bentley University and the author of “How Algorithms Create and Prevent Fake News.”

The Coming Wave

Technology, Power, and the Twenty-first Century’s Greatest Dilemma

By Mustafa Suleyman with Michael Bhaskar

Crown. 332 pp. $32.50

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