research-article

Trustworthy AI and the Logics of Intersectional Resistance

Authors:

Jasmine Fledderjohann,

John T. Richards,

Kush R. VarshneyAuthors Info & Claims

FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency

Pages 172 - 182

https://doi.org/10.1145/3593013.3593986

Published: 12 June 2023 Publication History

Abstract

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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Index Terms

Trustworthy AI and the Logics of Intersectional Resistance
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI theory, concepts and models
2. Social and professional topics
  1. Professional topics
    1. Computing profession

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FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency

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Benthall SShekman D(2023)Designing Fiduciary Artificial IntelligenceProceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization10.1145/3617694.3623230(1-15)Online publication date: 30-Oct-2023
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