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Cloud ethics = algorithms and the attributes of ourselves and others /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Cloud ethics/ Louise Amoore.
其他題名:	algorithms and the attributes of ourselves and others /
作者:	Amoore, Louise.
出版者:	Durham :Duke University Press, : c2020.,
面頁冊數:	1 online resource (232 p.)
標題:	Algorithms - Moral and ethical aspects. -
電子資源:	https://www.degruyter.com/isbn/9781478009276
ISBN:	9781478009276

Cloud ethics = algorithms and the attributes of ourselves and others /
Amoore, Louise.

Cloud ethicsalgorithms and the attributes of ourselves and others /[electronic resource] :Louise Amoore. - Durham :Duke University Press,c2020. - 1 online resource (232 p.)

Includes bibliographical references and index.

In Cloud Ethics Louise Amoore examines how machine learning algorithms are transforming the ethics and politics of contemporary society. Conceptualizing algorithms as ethicopolitical entities that are entangled with the data attributes of people, Amoore outlines how algorithms give incomplete accounts of themselves, learn through relationships with human practices, and exist in the world in ways that exceed their source code. In these ways, algorithms and their relations to people cannot be understood by simply examining their code, nor can ethics be encoded into algorithms. Instead, Amoore locates the ethical responsibility of algorithms in the conditions of partiality and opacity that haunt both human and algorithmic decisions. To this end, she proposes what she calls cloud ethics-an approach to holding algorithms accountable by engaging with the social and technical conditions under which they emerge and operate.

ISBN: 9781478009276

Standard No.: 10.1515/9781478009276doiSubjects--Topical Terms:

3674155
Algorithms
--Moral and ethical aspects.

LC Class. No.: QA76.585

Dewey Class. No.: 004.67/82

Cloud ethics = algorithms and the attributes of ourselves and others /
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520 $a In Cloud Ethics Louise Amoore examines how machine learning algorithms are transforming the ethics and politics of contemporary society. Conceptualizing algorithms as ethicopolitical entities that are entangled with the data attributes of people, Amoore outlines how algorithms give incomplete accounts of themselves, learn through relationships with human practices, and exist in the world in ways that exceed their source code. In these ways, algorithms and their relations to people cannot be understood by simply examining their code, nor can ethics be encoded into algorithms. Instead, Amoore locates the ethical responsibility of algorithms in the conditions of partiality and opacity that haunt both human and algorithmic decisions. To this end, she proposes what she calls cloud ethics-an approach to holding algorithms accountable by engaging with the social and technical conditions under which they emerge and operate.
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