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Publisher's Summary

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. Listeners 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. 

©2020 Brian Christian (P)2020 Brilliance Publishing, Inc., all rights reserved.

What listeners say about The Alignment Problem

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  • Ahmed ELGazzar
  • 2021-11-04

One of the best outlook books on AI

It was a pleasure listening to the book. It's cosncie enough to suit experts in the field and also offer a broad general overview if you don't know much about the current state of AI. Particularly enjoyes the chapters on RL

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  • ehan ferguson
  • 2020-11-16

Required reading for any AI course

Brian Christian’s holistic approach is approachable to wide audience both technical and otherwise. I read this book while also taking an AI course in college. This book alone easily surpassed what I learned in that course. That’s not even mentioning the methodological and philosophical knowledge picked up from this read. Brian Christian is easily the Malcom Gladwell of computational philosophy.

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  • Anonymous User
  • 2022-04-07

Too much to process

Brought this book after listening to some good reads from Brian Christian. But this was way below my expectation. I could not complete it.

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  • Amazon Customer
  • 2022-02-14

Clear and thought provoking

I enjoy listening to books read by the author - they are the authority on how to convey the importance of the material. And this is very, very important material and concepts. This is an excellent book,not just for understanding the potential risks and challenges of teaching (and coexisting and thriving with) our intelligent machines, but also as a clear and concise history and background of the development of artificial intelligence algorithms. Please read/listen to it- it is the responsibility of an informed citizenry to become familiar with these issues.

l had read books about the dangers of bias in AI applications, and indeed that is explained here as well (with a clearer technical background than most of those other books). But this book goes beyond these cautionary cases to explain, clearly, the root challenges that can lead to biases (and much greater disasters) and the likely pathways to solutions. These pathways are developed via well-explained explorations of machine epistemological theories and learning mechanisms, building from social, psychological and in some cases neurological concepts, to computational ideas.

This book is already helping me to add new and forward-looking concepts to the university course I teach on risk assessment in engineered systems, as well as a course I co-teach with faculty from humanities disciplines on the nature of knowledge. Thank you!

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  • Casey
  • 2021-11-29

Must read/listen

The book dives deep into AI and machine learning. Excellent story, excellently written. In some ways it is humanity's most pressing topic.

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  • Amazon Customer
  • 2021-08-28

Interesting overall

I liked the subject of the book. I also liked the ideas and stories shared in it.

However, the book ultimately came across as a summarization of research over the last 100 years related to machine learning and artificial intelligence -- instead of a what I expected to be an in depth description of the potential severity of the "alignment problem" in a modern or future context.

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  • Mohammad Mobasher Hossain
  • 2021-06-15

I am a huge fan of Brian Christian.

I am a huge fan of Brian Christian. So all my reviews will be biased. :)

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  • Patrick
  • 2022-08-02

An amazing look into decision making of human and computers

I was expecting a book on machine learning and computer ethics with a tale of interesting examples. What I got was far more insight into the learning biological machine that we as humans are. It did touch on the mistakes of ML training and how techniques have developed so for those worried it wouldn’t cover that it does - in not overly technical language. I highly recommend it though as it weaves in neuro-physiology and psychological in such an interesting way. A great read for all.

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  • Ran Away
  • 2022-07-18

Very enlightening

I learned a great deal about artificial intelligence reading this book including current big ideas, and clearly presented ethical and practical challenges in designing and implementing AI. The author’s narration was engaging and clear.

I strongly recommend this book and audiobook.

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  • Mike Lawrence
  • 2022-07-14

Solid book

Great overview of machine learning as it relates to the difficulties implementing human preferences, but little on the threat of ai as an existential issue