The alignment problem : machine learning and human values /

The alignment problem : machine learning and human values /

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Bibliographic Details
Author / Creator:	Christian, Brian, 1984- author.
Imprint:	New York, NY : W.W. Norton & Company, [2021] ©2020
Description:	xvi, 476 pages ; 21 cm
Language:	English
Subject:	Artificial intelligence -- Moral and ethical aspects. Artificial intelligence -- Social aspects. Machine learning -- Safety measures. Software failures. Social values. Social Values Artificial intelligence -- Moral and ethical aspects. Artificial intelligence -- Social aspects. Social values. Software failures.
Format:	Print Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/13441485

Hidden Bibliographic Details
Varying Form of Title:	Machine learning and human values
ISBN:	9780393868333 0393868338
Notes:	Includes bibliographical references (pages [401]-451) and index.
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. 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 autonomous vehicles on our streets can injure or kill. When 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. 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"--

Table of Contents:

Prologue
Introduction
I. Prophecy
1. Representation
2. Fairness
3. Transparency
II. Agency
4. Reinforcement
5. Shaping
6. Curiosity
III. Normativity
7. Imitation
8. Inference
9. Uncertainty
Conclusion
Acknowledgments
Notes
Bibliography
Index