mlsanityData to 14 Oct 2026

Recentering Validity Considerations through Early-Stage Deliberations Around AI and Policy Design

arXiv 2303.14602 ↗First posted 26 Mar 2023cs.HC cs.AIcited by 0

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Abstract (arXiv)

AI-based decision-making tools are rapidly spreading across a range of real-world, complex domains like healthcare, criminal justice, and child welfare. A growing body of research has called for increased scrutiny around the validity of AI system designs. However, in real-world settings, it is often not possible to fully address questions around the validity of an AI tool without also considering the design of associated organizational and public policies. Yet, considerations around how an AI tool may interface with policy are often only discussed retrospectively, after the tool is designed or deployed. In this short position paper, we discuss opportunities to promote multi-stakeholder deliberations around the design of AI-based technologies and associated policies, at the earliest stages of a new project.

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References · 9

  1. 2022The Fallacy of AI Functionalitycited by 88
  2. 2020A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scorescited by 74
  3. 2019Unremarkable AI: Fitting Intelligent Decision Support into Critical, Clinical Decision-Making Processescited by 53
  4. 2022Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Supportcited by 39
  5. 2022A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithmscited by 30
  6. 2021Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systemscited by 27
  7. 2021Algorithms and Decision-Making in the Public Sectorcited by 20
  8. 2021Designing for human-AI complementarity in K-12 educationcited by 19
  9. 2021Leveraging Expert Consistency to Improve Algorithmic Decision Supportcited by 17

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