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Understanding Practices, Challenges, and Opportunities for User-Engaged Algorithm Auditing in Industry Practice (2210.03709v4)

Published 7 Oct 2022 in cs.HC, cs.AI, and cs.LG

Abstract: Recent years have seen growing interest among both researchers and practitioners in user-engaged approaches to algorithm auditing, which directly engage users in detecting problematic behaviors in algorithmic systems. However, we know little about industry practitioners' current practices and challenges around user-engaged auditing, nor what opportunities exist for them to better leverage such approaches in practice. To investigate, we conducted a series of interviews and iterative co-design activities with practitioners who employ user-engaged auditing approaches in their work. Our findings reveal several challenges practitioners face in appropriately recruiting and incentivizing user auditors, scaffolding user audits, and deriving actionable insights from user-engaged audit reports. Furthermore, practitioners shared organizational obstacles to user-engaged auditing, surfacing a complex relationship between practitioners and user auditors. Based on these findings, we discuss opportunities for future HCI research to help realize the potential (and the mitigate risks) of user-engaged auditing in industry practice.

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Authors (6)
  1. Wesley Hanwen Deng (15 papers)
  2. Bill Boyuan Guo (1 paper)
  3. Alicia DeVrio (6 papers)
  4. Hong Shen (120 papers)
  5. Motahhare Eslami (27 papers)
  6. Kenneth Holstein (37 papers)
Citations (43)

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