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Strategies for Increasing Corporate Responsible AI Prioritization (2405.03855v2)

Published 6 May 2024 in cs.CY

Abstract: Responsible artificial intelligence (RAI) is increasingly recognized as a critical concern. However, the level of corporate RAI prioritization has not kept pace. In this work, we conduct 16 semi-structured interviews with practitioners to investigate what has historically motivated companies to increase the prioritization of RAI. What emerges is a complex story of conflicting and varied factors, but we bring structure to the narrative by highlighting the different strategies available to employ, and point to the actors with access to each. While there are no guaranteed steps for increasing RAI prioritization, we paint the current landscape of motivators so that practitioners can learn from each other, and put forth our own selection of promising directions forward.

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Authors (3)
  1. Angelina Wang (24 papers)
  2. Teresa Datta (5 papers)
  3. John P. Dickerson (78 papers)
Citations (2)
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