Trustworthy AI and the Logics of Intersectional Resistance
Trustworthy AI and the Logics of Intersectional Resistance
复制标题
值得信赖的人工智能和交叉阻力的逻辑
DOI:
10.1145/3593013.3593986
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发表时间:
2023
期刊:
影响因子:
--
通讯作者:
Knowles B
中科院分区:
文献类型:
--
作者:
Knowles B
Growing awareness of the capacity of AI to inflict harm has inspired efforts to delineate principles for ‘trustworthy AI’ and, from these, objective indicators of ‘trustworthiness’ for auditors and regulators. Such efforts run the risk of formalizing a distinctly privileged perspective on trustworthiness which is insensitive (or else indifferent) to the legitimate reasons for distrust held by marginalized people. By exploring a neglected conative element of trust, we broaden understandings of trust and trustworthiness to make sense of, and identify principles for responding productively to, distrust of ostensibly ‘trustworthy’ AI. Bringing social science scholarship into dialogue with AI criticism, we show that AI is being used to construct a digital underclass that is rhetorically labelled as ‘undeserving’, and highlight how this process fulfills functions for more privileged people and institutions. We argue that distrust of AI is warranted and healthy when the AI contributes to marginalization and structural violence, and that Trustworthy AI may fuel public resistance to the use of AI unless it addresses this dimension of untrustworthiness. To this end, we offer reformulations of core principles of Trustworthy AI—fairness, accountability, and transparency—that substantively address the deeper issues animating widespread public distrust of AI, including: stewardship and care, openness and vulnerability, and humility and empowerment. In light of legitimate reasons for distrust, we call on the field to to re-evaluate why the public would embrace the expansion of AI into all corners of society; in short, what makes it worthy of their trust.
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DOI:
--
发表时间:
2014
期刊:
影响因子:
--
作者:
Kouki Kiyota;Hironori Ueno;Keiko Numayama-Tsuruta;Yohsuke Imai;Takami Yamaguchi;Takuji Ishikawa;北川進
通讯作者:
北川進
影响因子:
2.9
作者:
Sandra Wachter;B. Mittelstadt;Chris Russell
通讯作者:
Chris Russell
DOI:
10.1145/3442188.3445870
发表时间:
2021
期刊:
Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
影响因子:
--
作者:
J. Park;Danielle Bragg;Ece Kamar;M. Morris
通讯作者:
M. Morris
DOI:
--
发表时间:
2021
期刊:
International Conference on Human Factors in Computing Systems
影响因子:
--
作者:
Min Kyung Lee;Kate Rich
通讯作者:
Kate Rich
DOI:
--
发表时间:
2003
期刊:
影响因子:
--
作者:
Angela Davis
通讯作者:
Angela Davis