Understanding Contestability on the Margins: Implications for the Design of Algorithmic Decision-making in Public Services

要旨

Policymakers have established that the ability to contest decisions made by or with algorithms is core to responsible artificial intelligence (AI). However, there has been a disconnect between research on contestability of algorithms, and what the situated practice of contestation looks like in contexts across the world, especially amongst communities on the margins. We address this gap through a qualitative study of follow-up and contestation in accessing public services for land ownership in rural India and affordable housing in the urban United States. We find there are significant barriers to exercising rights and contesting decisions, which intermediaries like NGO workers or lawyers work with communities to address. We draw on the notion of accompaniment in global health to highlight the open-ended work required to support people in navigating violent social systems. We discuss the implications of our findings for key aspects of contestability, including building capacity for contestation, human review, and the role of explanations. We also discuss how sociotechnical systems of algorithmic decision-making can embody accompaniment by taking on a higher burden of preventing denials and enabling contestation.

著者
Naveena Karusala
Harvard University, Allston, Massachusetts, United States
Sohini Upadhyay
Harvard University, Allston, Massachusetts, United States
Rajesh Veeraraghavan
Georgetown University, Washington DC, District of Columbia, United States
Krzysztof Z.. Gajos
Harvard University, Allston, Massachusetts, United States
論文URL

doi.org/10.1145/3613904.3641898

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Remote Presentations: Highlight on AI

Remote Sessions
14 件の発表
2024-05-13 18:00:00
2024-05-14 02:20:00