The Alignment Problem Front Cover
Stuart Russell, UC Berkeley
Hannah Fry, The New Yorker
Publishers Weekly
Mike Krieger, Instagram
Required reading
Jennifer Pahlka, Code for America
Jaan Tallinn, Skype
Tim O’Reilly, O’Reilly Media

Winner, Excellence in Science Communication Award
National Academies of Sciences, Engineering, and Medicine

Finalist, Best Science & Technology Book of the Year
Los Angeles Times
This is the book on artificial intelligence we need right now
Mike Krieger, cofounder of Instagram
Clear and compelling. ... Moves us from the theoretical to the practical while attempting to answer one of our industry’s most pressing questions
Satya Nadella, CEO of Microsoft
The Alignment Problem is the best book on the key technical and moral questions of A.I. that I’ve read
Ezra Klein, The New York Times
Fascinating, provocative, and insightful. Essential reading if you want to understand where our world is heading
Stuart Russell, author of Artificial Intelligence: A Modern Approach
Meticulously researched and superbly written
There’s no better book than The Alignment Problem at spelling out the issues of governing AI safely
James Barrat, best-selling author of Our Final Invention
A nuanced and captivating exploration of this white-hot topic
The Wall Street Journal
Brian Christian is a fine writer and has produced a fascinating book. AI seems destined to become, for good or ill, increasingly prominent in our lives. We should be grateful for this balanced and hype-free perspective on its scope and limits
Martin Rees, Emeritus Professor of Cosmology and Astrophysics, University of Cambridge
Masterfully surveys the ‘AI fairness’ community, introducing us to some of its main characters, some of its historical roots, and crucially, many of its philosophical quandaries and limitations
Cathy O’Neil, author of Weapons of Math Destruction
Riveting and deeply complex. A helpful guide to an urgent problem
Publishers Weekly
Required reading for anyone influencing policy where algorithms are in play. A delight to read
Jennifer Pahlka, founder of Code for America and former deputy CTO of the United States
Essential reading. Christian brings much needed clarity to a subject that is often talked about but little understood
Tim O’Reilly, founder and CEO of O’Reilly Media
Abundantly researched and captivating. Rich with surprising discoveries, unexpected obstacles, ingenious solutions and, increasingly, hard questions about the soul of our species
Jaan Tallinn, cofounder of Skype and the Future of Life Institute

A jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them.

Today’s “machine-learning” systems, trained by data, are so effective that we’ve invited them to see and hear for us—and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem.

Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole—and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands.

The mathematical and computational models driving these changes range in complexity from something that can fit on a spreadsheet to a complex system that might credibly be called “artificial intelligence.” They are steadily replacing both human judgment and explicitly programmed software.

In best-selling author Brian Christian’s riveting account, we meet the alignment problem’s “first-responders,” and learn their ambitious plan to solve it before our hands are completely off the wheel. In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Readers encounter a discipline finding its legs amid exhilarating and sometimes terrifying progress. Whether they―and we―succeed or fail in solving the alignment problem will be a defining human story.

The Alignment Problem offers an unflinching reckoning with humanity’s biases and blind spots, our own unstated assumptions and often contradictory goals. A dazzlingly interdisciplinary work, it takes a hard look not only at our technology but at our culture―and finds a story by turns harrowing and hopeful.