mlsanityData to 7 Oct 2026

On the Quest for Effectiveness in Human Oversight: Interdisciplinary Perspectives

arXiv 2404.04059 ↗First posted 5 Apr 2024cs.CYcited by 28

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Abstract (arXiv)

Human oversight is currently discussed as a potential safeguard to counter some of the negative aspects of high-risk AI applications. This prompts a critical examination of the role and conditions necessary for what is prominently termed effective or meaningful human oversight of these systems. This paper investigates effective human oversight by synthesizing insights from psychological, legal, philosophical, and technical domains. Based on the claim that the main objective of human oversight is risk mitigation, we propose a viable understanding of effectiveness in human oversight: for human oversight to be effective, the oversight person has to have (a) sufficient causal power with regard to the system and its effects, (b) suitable epistemic access to relevant aspects of the situation, (c) self-control, and (d) fitting intentions for their role. Furthermore, we argue that this is equivalent to saying that an oversight person is effective if and only if they are morally responsible and have fitting intentions. Against this backdrop, we suggest facilitators and inhibitors of effectiveness in human oversight when striving for practical applicability. We discuss factors in three domains, namely, the technical design of the system, individual factors of oversight persons, and the environmental circumstances in which they operate. Finally, this paper scrutinizes the upcoming AI Act of the European Union -- in particular Article 14 on Human Oversight -- as an exemplary regulatory framework in which we study the practicality of our understanding of effective human oversight. By analyzing the provisions and implications of the European AI Act proposal, we pinpoint how far that proposal aligns with our analyses regarding effective human oversight as well as how it might get enriched by our conceptual understanding of effectiveness in human oversight.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Apr 2024.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 9; 2026: 16.

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  1. 2024Privacy Leakage Overshadowed by Views of AI: A Study on Human Oversight of Privacy in Language Model Agentcited by 14
  2. 2025Inherent and emergent liability issues in LLM-based agentic systems: a principal-agent perspectivecited by 12
  3. 2024Don't be Fooled: The Misinformation Effect of Explanations in Human-AI Collaborationcited by 8
  4. 2025Formalising Human-in-the-Loop: Computational Reductions, Failure Modes, and Legal-Moral Responsibilitycited by 7
  5. 2026Position: Human-Centric AI Requires a Minimum Viable Level of Human Understandingcited by 6
  6. 2026Human oversight of agentic systems in practice: Examining the oversight work, challenges, and heuristics of developers using software agentscited by 6
  7. 2025Accountability Capture: How Record-Keeping to Support AI Transparency and Accountability (Re)shapes Algorithmic Oversightcited by 5
  8. 2025AI and Human Oversight: A Risk-Based Framework for Alignmentcited by 4
  9. 2026AI Agents Push Humans Out of the Loopcited by 3
  10. 2026Keeping an Eye on AI: A Framework for Effective Human Oversight of AI Systemscited by 2
  11. 2025Contemplative Artificial Intelligencecited by 1
  12. 2025Leveraging LLMs to Streamline the Review of Public Funding Applicationscited by 1
16 more
  1. 2026A Framework for Measuring Appropriate Reliance on Set-Valued AI Advicecited by 1
  2. 2026Engineering Reliable Coding Agents: Evaluating and Operating the System Around the Modelcited by 1
  3. 2024Vision Paper: Designing Graph Neural Networks in Compliance with the European Artificial Intelligence Actcited by 0
  4. 2025Exploring Moral Exercises for Human Oversight of AI systems: Insights from Three Pilot Studiescited by 0
  5. 2025Unequal Uncertainty: Rethinking Algorithmic Interventions for Mitigating Discrimination from AIcited by 0
  6. 2025The SMART+ Framework for AI Systemscited by 0
  7. 2026Intelligent support for Human Oversight: Integrating Reinforcement Learning with Gaze Simulation to Personalize Highlightingcited by 0
  8. 2026Where are the Humans? A Scoping Review of Fairness in Multi-agent AI Systemscited by 0
  9. 2026Modularizing Educational LLM-Agency for Fostering Responsible Learning Assistancecited by 0
  10. 2026AI Assurance in UK Defence: Challenges in Operationalising JSP 936cited by 0
  11. 2026Security and Privacy in Agentic AI: Grand Challenges and Future Directionscited by 0
  12. 2026The Human Utility Factor: A Computable Welfare Metric That Reframes AI Governance as a Constrained Optimisation Problemcited by 0
  13. 2026Epistemic Trustworthiness in Generative AI: A Normative Framework for Warranted Reliance in High-Stakes Workflowscited by 0
  14. 2026LAAF: A Layered Accountability Architecture Framework for LLM Applicationscited by 0
  15. 2026Norms at a Price: Why RL-Based Alignment Can Promise Conditional Compliance at Bestcited by 0
  16. 2026Anticipatory Human Oversight of Agentic AI: A Philosophical Accountcited by 0