If Anyone Builds It, Everyone Dies

The most important book I’ve read for years: I want to bring it to every political and corporate leader in the world and stand over them until they’ve read it. Yudkowsky and Soares, who have studied AI and its possible trajectories for decades, sound a loud trumpet call to humanity to awaken us as we sleepwalk into disaster. Their brilliant gift for analogy, metaphor and parable clarifies for the general reader the tangled complexities of AI engineering, cognition and neuroscience better than any book on the subject I’ve ever read, and I’ve waded through scores of them. We really must rub our eyes and wake the fuck up! – Stephen FryShould you worry about superintelligent AI? The answer from one of the tech world’s most influential doomsayers, Eliezer Yudkowsky, is emphatically yes. The good news? We aren’t there yet, and there are still steps we can take to avert disaster * Guardian ** Biggest Books of the Autumn ** *The most important book of the decade … This captivating page-turner, from two of today’s clearest thinkers, reveals that the competition to build smarter-than-human machines isn’t an arms race but a suicide race, fuelled by wishful thinking – Max Tegmark, author of Life 3.0If Anyone Builds It, Everyone Dies may prove to be the most important book of our time. Yudkowsky and Soares believe we are nowhere near ready to make the transition to superintelligence safely, leaving us on the fast track to extinction. Through the use of parables and crystal-clear explainers, they convey their reasoning, in an urgent plea for us to save ourselves while we still can – Tim Urban, co-founder of Wait But WhyGiven the gravity of the case [Yudkowsky and Soares] make, it feels an odd thing to say that this book is good. It is readable. It tells stories well. At points it is like a thriller – albeit one where the thrills come from the obliteration of literally everything of value … This is the apocalypse du jour … The achievement of this book is, given the astonishing claims they make, that they make a credible case for not being mad. But I really hope they are: because I can’t see a way we get off that ladder. * The Times *The authors tell their story with clarity, verve and a kind of barely suppressed glee. For a book about human extinction, If Anyone Builds It, Everyone Dies is a lot of fun. – Ian Leslie * Observer *Despite the complexity of its subject, If Anyone Builds It, Everyone Dies is as clear as its conclusions are hard to swallow…everyone with an interest in the future has a duty to read what Yudkowsky and Soares have to say. – David Shariatmadari * Guardian, Book of the Day *The best no-nonsense, simple explanation of the AI risk problem I’ve ever read – Yishan Wong, former CEO of RedditSoares and Yudkowsky lay out, in plain and easy-to-follow terms, why our current path toward ever-more-powerful AIs is extremely dangerous – Emmett Shear, former interim CEO of OpenAIAn eloquent and urgent plea for us to step back from the brink of self-annihilation – Fiona Hill, Defence Advisor to UK government

Eliezer Yudkowsky (Author)

Eliezer Yudkowsky is a founding researcher of the field of AI alignment, with influential work spanning more than twenty years. As co-founder of the non-profit Machine Intelligence Research Institute (MIRI), Yudkowsky sparked early scientific research on the problem and has played a major role in shaping the public conversation about smarter-than-human AI. He appeared on Time magazine’s 2023 list of the 100 Most Influential People In AI, and has been discussed or interviewed in the New York Times, New Yorker, Newsweek, Forbes, Wired, Bloomberg, The Atlantic, The Economist, Washington Post, and elsewhere.

Nate Soares (Author)

Nate Soares is the president of the non-profit Machine Intelligence Research Institute (MIRI). He has been working in the field for over a decade, after previous experience at Microsoft and Google. Soares is the author of a large body of technical and semi-technical writing on AI alignment, including foundational work on value learning, decision theory, and power-seeking incentives in smarter-than-human AIs.