The Alignment Problem Titelbild

The Alignment Problem

Machine Learning and Human Values

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The Alignment Problem

Von: Brian Christian
Gesprochen von: Brian Christian
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Über diesen Titel

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.
Geschichte & Kultur Informatik Wissenschaft

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By far the best book I have read/heard in the past years. If you want to understand the complexity and simplicity of AI, this is a must-read. If you favor tech solutions, you will learn about their limits. And if you are afraid of giving up too much on machines, you will discover that the field of AI has learned a lot about how they create systems in favor of humans and care about responsibility.

Insightful for experts and novices in AI

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Great narrative to a highly interesting topic! The examples were alaways very helpful! I would have expected though more on the big picture and the movement around superintelligence.

Great introduction to the field

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I have rarely retained so much from one singular book ; great and interesting topic helped a great deal with research for my thesis

So very interesting

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Very helpful referring to myself as being a father a colleague and man, The book informs about the history, difficulties and pitfalls of machine learning as well as how we ourselves learn and our imperfections with it.

Inspiring

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The book is very deceptive. You might think it's about machine learning, but actually, machine learning is just a tool through which diverse topics are explored in a fresh and enlightening manner, including curiosity or fairness. Highly recommend!

Know thyself through thy machines

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Please, Audio book publishers: Don’t let authors read their own books. While that’s really nice for a prologue or introduction, it’s super annoying to suffer through a whole book listening to a non-trained monotonous reader

Great content, bad reader

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