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

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Abstract

Policymakers have established that the ability to contest decisions made by or with algorithms is core to responsible artifcial 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 afordable housing in the urban United States. We fnd there are signifcant 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 fndings 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.

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APA

Karusala, N., Upadhyay, S., Veeraraghavan, R., & Gajos, K. (2024). Understanding Contestability on the Margins: Implications for the Design of Algorithmic Decision-making in Public Services. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. https://doi.org/10.1145/3613904.3641898

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