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Brian Christian
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The Alignment Problem: Machine Learning and Human Values 1st Edition

by Brian Christian (Author)

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Finalist for the Los Angeles Times Book Prize

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.

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  1. ISBN-10
    0393635821
  2. ISBN-13
    978-0393635829
  3. Edition
    1st
  4. Publisher
    W. W. Norton & Company
  5. Publication date
    October 6, 2020
  6. Language
    English
  7. Dimensions
    6.5 x 1.7 x 9.6 inches
  8. Print length
    496 pages
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The Alignment Problem - Brian Christian

The Alignment Problem - Brian Christian

The Alignment Problem - Brian Christian

Editorial Reviews

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"The disconnect between intention and results―between what mathematician Norbert Wiener described as 'the purpose put into the machine' and 'the purpose we really desire'―defines the essence of 'the alignment problem.' Brian Christian, an accomplished technology writer, offers a nuanced and captivating exploration of this white-hot topic, giving us along the way a survey of the state of machine learning and of the challenges it faces."
― David A. Shaywitz, Wall Street Journal

"[C]lear and compelling...The storytelling here moves us from the theoretical to the practical while attempting to answer one of our industry's most pressing questions: How do we teach machines, and what should we teach them?"
― Satya Nadella, Fast Company

"A fascinating, provocative, and insightful tour of all the ways that AI goes wrong and all the ways people are trying to fix it. Essential reading if you want to understand where our world is heading."
― Stuart Russell, professor of computer science, University of California, Berkeley, and author of Human Compatible

"A new field has emerged that responds to and scrutinizes the vast technological shifts represented by our modern, virtual, algorithmically defined world. In The Alignment Problem, Brian Christian masterfully surveys the ‘AI fairness’ community, introducing us to some of its main characters; some of its historical roots in science, philosophy, and activism; and crucially, many of its philosophical quandaries and limitations."
― Cathy O’Neil, author of Weapons of Math Destruction

"This is the book on artificial intelligence we need right now. Brian Christian takes us on a technically fluent (yet widely accessible) journey through the most important questions facing AI and humanity. It is thought-provoking and vital reading for anyone interested in our future."
― Mike Krieger, cofounder of Instagram

"An abundantly researched and captivating book that explores the road humanity has taken to create a successor for itself―a road that’s 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

"The Alignment Problem should be required reading for anyone influencing policy where algorithms are in play―which is everywhere. But unlike much required reading, the book is a delight to read, a playful romp through personalities and relatable snippets of science history that put the choices of our present moment into context."
― Jennifer Pahlka, founder of Code for America and former deputy CTO of the United States

"A deeply enjoyable and meticulously researched account of how computer scientists and philosophers are defining the biggest question of our time: how will we create intelligent machines that will improve our lives rather than complicate or even destroy them? 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

"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

"An intriguing exploration of AI, which is advancing faster than―well, than we are."
― Kirkus Reviews

About the Author

Brian Christian is the author of the acclaimed bestsellers The Most Human Human and Algorithms to Live By, which have been translated into nineteen languages. A visiting scholar at the University of California, Berkeley, he lives in San Francisco.

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About the author

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Brian Christian

Brian Christian

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Brian Christian is the author of the acclaimed bestsellers "The Most Human Human," a New York Times editors’ choice and a New Yorker favorite book of the year, and "Algorithms to Live By" (with Tom Griffiths), a #1 Audible bestseller, Amazon best science book of the year and MIT Technology Review best book of the year.

Christian’s writing has appeared in The New Yorker, The Atlantic, Wired, and The Wall Street Journal, as well as peer-reviewed journals such as Cognitive Science. He has been featured on The Daily Show and Radiolab, and has lectured at Google, Facebook, Microsoft, the Santa Fe Institute, and the London School of Economics. His work has won several awards, including publication in Best American Science & Nature Writing, and has been translated into nineteen languages.

Christian holds degrees in computer science, philosophy, and poetry from Brown University and the University of Washington. A Visiting Scholar at the University of California, Berkeley, he lives in San Francisco.

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Top reviews from the United States

  • Descartes
    5.0 out of 5 stars Excellent (Even in 2025)
    Reviewed in the United States on July 24, 2025
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    While AI has advanced considerably since publishing of this book, the topics and ideas in this book are as relevant as ever. A fantastic read recommended for every computer scientist, AI researcher and ethical philosopher.
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  • Rachel Gollub
    4.0 out of 5 stars Excellent overview of alignment research
    Reviewed in the United States on November 23, 2023
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    This is an introduction to the alignment problem, and then an overview of the problems and solutions that have developed over time. It’s highly useful for anyone working in the AI/ML space, because it also has a lot of tips and tricks for solving common problems with models, and overviews of a lot of the major techniques that are used. (The chapters on reinforcement learning were worth it by themselves — a detailed description of the process and variables with examples). Overall, terrific read.
    3 people found this helpful
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  • Casey Dorman
    5.0 out of 5 stars Integrates a phenomenal amount of information from psychology and machine learning
    Reviewed in the United States on August 11, 2021
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    I must admit that I was taken by surprise by the contents of Brian Christian’s recent book, The Alignment Problem. The book came out in 2020 and made quite a splash among the artificial intelligence (AI) and machine intelligence community. Much of the public, including myself, had been made aware of “the alignment problem” by Nick Bostrom’s book, Superintelligence, or the writings of people such as MIT physicist, Max Tegmark. In fact, in my case, it was the conundrum of the alignment problem that spurred me to write my science fiction novel, Ezekiel’s Brain. Simply put, the alignment problem in the AI world is the question of how you create a superintelligent AI that is “friendly,” i.e., helpful rather than dangerous, to humanity. It’s such a difficult question that, in my novel, Ezekiel’s Brain, the creators of the superintelligent AI fail, and the result is disastrous for the human race. What I was expecting from Brian Christian’s book was another description of the nightmare scenarios of the kind I wrote about in my novel, and experts such as Bostrom and Tegmark talk about in their writings. That wasn’t what The Alignment Problem was about… or at least not what it was mostly about.

    Christian gives some detailed accounts of disastrous results applying the most sophisticated AI learning algorithms to actual human situations. Some of these are well-known, such as attempts to censor social media content, or to produce an algorithm that aided judges in criminal sentencing, or to develop screening tools for employment selection. Training AIs using data on human decisions simply amplified the biases, including gender, racial and ideological, we humans use to make our decisions. These were instances of AIs performing in a way that was more harmful than helpful to humans, and they were results of which I had previously only been vaguely aware. Although they were not the kind of misalignment that I was concerned with and had prompted me to buy the book, they expanded my concept of alignment considerably.

    Instead of providing nightmare scenarios of the danger of superintelligent AIs that are not aligned with what is best for humanity, the bulk of Christian’s book provides an exquisite history, up to the present, of the efforts of the AI community to define how machines can learn, what they are learning and what they ought to be learning, and how to identify whether the progress being made is bringing AIs in closer alignment with what humans want from them. What was most surprising and gratifying to me, as a psychologist, was how much this effort is entwined with progress in understanding how people learn and what affects that learning process.

    Christian writes his book like a good mystery, but rather than following a narrow plot, the breadth of inquiry is extraordinary. Even a psychologist, such as myself, learned about findings in psychology and learning and child development of which I was unaware. How computer scientists who develop AI use psychological findings to open up new avenues in machine learning is fascinating to hear about. The collaborations are thrilling, and both psychologists and AI researchers who are not aware of how much is happening on this front should read Christian’s book to get an idea of how exciting an important this area of research is becoming.

    Although I have some background related to psychology, AI, and the alignment problem, this book is written for the non-expert, and the interested layperson can easily understand it and bring their knowledge of the subject up to date. I found it one of the most captivating and informative books I have read in the last several years, and I recommend it for everyone for whom this topic sparks an interest.
    45 people found this helpful
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  • Marvin Gardens
    5.0 out of 5 stars Important, timely, well researched and written, 5 stars. Kindle translation: 2 stars.
    Reviewed in the United States on January 23, 2022
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    Not much to add to previous reviews. A fascinating, easy to read summary of efforts to understand and control how AI "agents" learn, informed by how the human brain develops and works. We still have an incomplete understanding of the latter, so it stands to reason there will be surprises in how machines learn and ways this can go awry. As Christian explains, this is proving to be the case and what just a few years ago were Hollywood doomsday scenarios like SkyNet in the Terminator movies - when machines become malevolent and work counter to human interests - have emerged as serious, genuine concerns and a rapidly expanding area of AI and machine learning research. Machine learning, coupled with advances in computer power, is expanding exponentially in capability and practitioners are increasingly worried about what is going on these "black boxes". I plan to re-read the book, to better understand the various facets of this. Best book I've read in awhile. THAT ALL BEING SAID, the Kindle version is a MESS! Hard returns/new paragraphs that shouldn't be there at least every couple of pages, and often more than one on a page, make it much harder to follow than it needs to be. This book is important and the apparent lack of proofreading is unacceptable!
    13 people found this helpful
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  • Klaus Gottlieb
    5.0 out of 5 stars The sorcerer's apprentices rummaging through Pandora's box
    Reviewed in the United States on October 16, 2020
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    I am a voracious reader, or should I say, listener because nowadays, I first listen to books which may be of interest. More often than not I find that popular business and even science books are large in volume but thin in content.
    The big exception is Brian Christian’s book “The Alignment Problem”, 1st Edition (October 6, 2020). Briefly, Christian defines the alignment problem as arising from our imprecise or incomplete instructions to artificial intelligence which may result in a potentially catastrophic divergence from what we really want and what AI actually does. Alignment ensures that models capture our norms and values so that they implement what we mean, intend and want.
    Christian’s narrative, always compelling and interesting, opens up new insights on every page even if you are generally familiar with the field. The book extends over 334 pages and is then followed by an 117 page notes and bibliography section. In other words, this huge accomplishment of a book is of value to the academic researcher in AI, ethicists and legal scholars, the advanced analytics practitioner and their managers, and an interested lay audience. It should be noted that the book is also of particular interest to physicians who are currently developing or using AI algorithms for diagnosis or patient management.
    Artificial intelligence is currently on the top of its own hype cycle again. In contrast to previous decades we now see an avalanche of real world applications covering up the potential for failure: obvious, patent, and potentially fixable, on one hand, and latent, hidden or lurking, waiting to trigger catastrophe, on the other hand. Raising awareness now will help avoid serious mistakes.
    30 people found this helpful
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Top reviews from other countries

  • Christoph Kenntemich
    5.0 out of 5 stars A great overview on how broad and complex a field machine learning truly is.
    Reviewed in Germany on March 26, 2023
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    I got progressively more interested, the further I advanced in the book.

    Also the hardcover is light blue, which has an appeal to me.
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  • Emidio Stani
    5.0 out of 5 stars Immersive flow in the continuous research of the alignment
    Reviewed in France on July 1, 2022
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    This book deals with the alignment problem analyzed in different perspectives over time while scaling out its abstraction and complexity.

    Being an IT person, I am fascinated by what machine learning has reached so far and what yet needs to be done for AI to be integrated in our society.

    The book does not require technical knowledge and I recommend it to anyone interested in machine learning, data engineering but also in policy making around AI.

    I like the style of the book, in part historical with a lot of references, and having for me the right speed of reading without stopping by too much on a topic.
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  • Georgina
    5.0 out of 5 stars Good introductory text to the issues
    Reviewed in Australia on April 23, 2021
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    Trying to understand alignment of human values and machine learning
    It’s a great eye opener and easy to understand - covers a lot of ground
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  • Dan Ryan
    5.0 out of 5 stars Smart, Informed, and Really Well-Written
    Reviewed in Canada on February 10, 2022
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    One of the best books around on AI alignment, especially for the non-technical expert. But Christian did such thorough research and explains things so authoritatively and clearly and brings in the voice of the experts from whom he learned that even experts will enjoy and benefit from this review of the field. Learned a lot. I may well assign it as a reading my teaching and I only do that for books that I think students will really get a lot out of.
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  • bnjasim
    1.0 out of 5 stars Philosophy is useless anyway!
    Reviewed in India on November 11, 2024
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    Don't read a book, rather DO something. Philosophy is useless!
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