Keeping an Eye on AI: A Framework for Effective Human Oversight of AI Systems
Not on the map. Why?
Abstract (arXiv)
The use of Artificial Intelligence (AI) in high-risk, decision-making scenarios presents technical, safety, and normative challenges; problems that may only be ameliorated by human oversight. However, notions of human oversight lack a common foundational understanding: oversight architectures are not well defined, the roles involved remain unclear, and implementation steps are opaque. Hence, researchers and practitioners struggle to determine how to design, implement, and evaluate systems that enable effective human oversight. This paper advances a practical framework for effective human oversight of AI systems, based on a cross-disciplinary perspective that draws on insights from computer science, human-computer interaction, psychology, philosophy, and law. The core contributions are: (1) a foundational framework, with a working definition, architecture and processes for effective human oversight of AI systems; (2) an initial template for documenting oversight architectures and processes, applied to diverse domains; and (3) a synthesis of open research challenges that need to be considered in the emerging field of effective human oversight of AI systems.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 17 of its 87 references that are in the map. First posted on arXiv 9 Apr 2026.
Builds on
17 of 87 references.
References · 17
- 2025Multi-Agent Risks from Advanced AIcited by 150
- 2022Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reductioncited by 137
- 2024When combinations of humans and AI are useful: A systematic review and meta-analysiscited by 100
- 2020A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scorescited by 74
- 2023Explainable AI is Dead, Long Live Explainable AI! Hypothesis-driven decision supportcited by 65
- 2021The Flaws of Policies Requiring Human Oversight of Government Algorithmscited by 44
- 2023Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systemscited by 40
- 2022Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theorycited by 32
- 2024On the Quest for Effectiveness in Human Oversight: Interdisciplinary Perspectivescited by 28
- 2023Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experiencecited by 18
- 2023Why Do Probabilistic Clinical Models Fail To Transport Between Sites?cited by 9
- 2025Automation Bias in the AI Act: On the Legal Implications of Attempting to De-Bias Human Oversight of AIcited by 7
5 more
- 2025Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigorcited by 7
- 2026Breaking Up with Normatively Monolithic Agency with GRACE: A Reason-Based Neuro-Symbolic Architecture for Safe and Ethical AI Alignmentcited by 5
- 2024A Survey of AI Reliancecited by 4
- 2025Monitoring Machine Learning Systems: A Multivocal Literature Reviewcited by 4
- 2025On the Complexities of Testing for Compliance with Human Oversight Requirements in AI Regulationcited by 2
Built on by
Citing papers per year: 2026: 2.
2 papers.