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The Alignment Problem: Machine Learning and Human Values
XPF 2294
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- 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.
| Publisher | Norton & Company |
| Publication date | 5 Oct. 2021 |
| Language | English |
| Print length | 496 pages |
| ISBN-10 | 0393868338 |
| ISBN-13 | 978-0393868333 |
| Item weight | 399 g |
| Dimensions | 13.97 x 3.05 x 21.08 cm |
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Paperback Ethics Editorial Review
The Alignment Problem: Machine Learning and Human Values presents a thorough exploration of the challenges faced in ensuring that artificial intelligence aligns with human values. Brian Christian delves into various case studies where the implementation of machine learning algorithms led to unintended consequences, amplifying existing biases in decision-making processes. Readers appreciate how the book is accessible to non-experts, offering a captivating narrative intertwined with historical context about the evolution of AI. It adeptly balances technical insight with readability, making it suitable for anyone curious about the intersection of AI and societal impact. Reviews highlight its comprehensive nature and the author's ability to distill complex ideas into engaging prose, making it a recommended read.
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Pros
- Engaging narrative with a historical perspective
- Accessible to non-experts and laypersons
- Well-researched with authoritative insights
- Makes complex topics easy to understand
Cons
- Some readers may desire more technical depth
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