mlsanityData to 7 Oct 2026

When Should Algorithms Resign? A Proposal for AI Governance

arXiv 2402.18326 ↗First posted 28 Feb 2024cs.CY cs.AIcited by 6

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Abstract (arXiv)

Algorithmic resignation is a strategic approach for managing the use of artificial intelligence (AI) by embedding governance directly into AI systems. It involves deliberate and informed disengagement from AI, such as restricting access AI outputs or displaying performance disclaimers, in specific scenarios to aid the appropriate and effective use of AI. By integrating algorithmic resignation as a governance mechanism, organizations can better control when and how AI is used, balancing the benefits of automation with the need for human oversight.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 1 of its 12 references that are in the map. First posted on arXiv 28 Feb 2024.

Builds on

1 of 12 references.

References · 1

  1. 2020Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Makingcited by 281

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 2.

6 papers.

  1. 2025Measuring and mitigating overreliance to build human-compatible AIcited by 9
  2. 2025Identifying, Evaluating, and Mitigating Risks of AI Thought Partnershipscited by 3
  3. 2025Revisiting Rogers' Paradox in the Context of Human-AI Interactioncited by 2
  4. 2025Unequal Uncertainty: Rethinking Algorithmic Interventions for Mitigating Discrimination from AIcited by 0
  5. 2026To Build or Not to Build? Factors that Lead to Non-Development or Abandonment of AI Systemscited by 0
  6. 2026Human-AI Teaming Through the Lens of Calibrationcited by 0