Trustworthy AI and the Logics of Intersectional Resistance

Trustworthy AI and the Logics of Intersectional Resistance
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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
Knowles B
中科院分区:
--
文献类型:
--
作者:
Knowles B

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越来越多的人意识到人工智能造成伤害的能力,这激发了人们努力描绘“值得信赖的人工智能”的原则,并从这些原则中为审计师和监管机构提供“可信度”的客观指标。这种努力有可能使一种对可信赖性的独特的特权观点正式化,这种观点对边缘化人群持有的不信任的正当理由不敏感(或漠不关心)。通过探索被忽视的信任的意动元素,我们扩大了对信任和可信度的理解,以理解并确定有效应对表面上“值得信赖”的AI的不信任的原则。将社会科学学术与人工智能批评对话,我们表明人工智能正在被用来构建一个被贴上“不值得”标签的数字下层阶级,并强调这一过程如何为更有特权的人和机构履行职能。我们认为,当人工智能导致边缘化和结构性暴力时,对人工智能的不信任是合理和健康的,值得信赖的人工智能可能会助长公众对人工智能使用的抵制,除非它解决了不值得信赖的这一问题。为此,我们重新制定了值得信赖的人工智能的核心原则-公平,问责和诚实-这些原则实质性地解决了引起公众对人工智能广泛不信任的更深层次问题,包括:管理和关怀,开放和脆弱性,以及谦卑和赋权。鉴于不信任的合理原因,我们呼吁该领域重新评估为什么公众会接受人工智能扩展到社会的各个角落;简而言之,是什么让它值得他们信任。
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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