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The alignment problem: machine learn...

Christian, Brian,

The alignment problem: machine learning and human values /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	The alignment problem: / edited by Brian Christian.
其他題名:	machine learning and human values /
作者:	Christian, Brian,
出版者:	New York, NY: W.W. Norton & Company, : 2020,
版本:	1st ed.
面頁冊數:	xii, 476 p.; 25cm;
提要註:	"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"--
標題:	Social values. -
ISBN:	9780393635829(hard):

The alignment problem: machine learning and human values /
Christian, Brian,

The alignment problem: machine learning and human values /edited by Brian Christian. - 1st ed. - New York, NY: W.W. Norton & Company, 2020 - xii, 476 p.; 25cm

Includes bibliographical references (p. [401]-451) and index.

"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"--

ISBN: 9780393635829(hard): NT588

LCCN: 2020029036Subjects--Topical Terms:

268819
Social values.

The alignment problem: machine learning and human values /
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245 1 4 $a The alignment problem: $b machine learning and human values / $c edited by Brian Christian.
250 $a 1st ed.
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300 $a xii, 476 p.; $c 25cm
504 $a Includes bibliographical references (p. [401]-451) and index.
520 # $a "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"-- $c Provided by publisher.
650 # 0 $2 96060 $a Social values. $3 268819
650 # 0 $a Software failures. $3 478207
650 # 0 $a Machine learning $x Safety measures. $3 478206
650 # 0 $a Artificial intelligence $x Social aspects. $3 478205
650 # 0 $a Artificial intelligence $x Moral and ethical aspects. $3 478187

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