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MR-034 Human & usage Both scope

Overreliance and automation bias

Users place uncritical trust in system outputs (automation bias), accepting incorrect results without verification.

Risk family
Human & usage
MIT domain
5. Human-Computer Interaction
MIT subdomain
5.1 > Overreliance and unsafe use
AI type
GPAI, Agentic, Classical_ML
Scope
Both
Source standard
MIT AI Risk Repository v4

Provenance

Source standard
MIT AI Risk Repository v4
MIT source entries
21 entries across 17 papers
  • Abercrombie2024A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms58.08.02
  • G'sell2024Regulating under Uncertainty: Governance Options for Generative AI47.02.12 47.02.13
  • Gabriel2024The Ethics of Advanced AI Assistants24.07.00
  • Giarmoleo2024What Ethics Can Say on Artificial Intelligence: Insights from a Systematic Literature Review37.02.00
  • Gipiškis2024Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems62.31.02
  • GOS2023Future Risks of Frontier AI56.14.00 56.18.00
  • IBM2025AI Risk Atlas65.15.03
  • Kumar2023Ethical Issues in the Development of Artificial Intelligence: Recognizing the Risks38.04.00
  • NIST2024Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile48.07.00
  • Paes2023Social Impacts of Artificial Intelligence and Mitigation Recommendations: An Exploratory Study10.08.00
  • Stanley2024Emerging Risks and Mitigations for Public Chatbots: LILAC v169.08.00 69.09.04
  • Tse2025Frontier AI Risk Management Framework (v1.0)72.02.01
  • Uuk2025A Taxonomy of Systemic Risks from General-Purpose AI61.02.08 61.02.28
  • Weidinger2022Taxonomy of Risks posed by Language Models16.05.02
  • Weidinger2023Sociotechnical Safety Evaluation of Generative AI Systems18.05.03
  • Wirtz2020The Dark Sides of Artificial Intelligence: An Integrated AI Governance Framework for Public Administration20.03.03
  • Wirtz2022Governance of artificial intelligence: A risk and guideline-based integrative framework19.04.05

Ev IDs of the entries consolidated into this risk in the MIT AI Risk Repository (V4); the source sheet row appears on hover.

ISO/IEC references
23894 obj A.3, A.12; src 4; mech B.4 | 42001 ctrl A.8.2

Framework crosswalk

Every framework item mapped to this risk. Items marked partial overlap only in part; definitions appear on hover where the source licence permits.

Sourcesframeworks that contributed to the register
2
  • A.12 ISO/IEC 23894 Annex A A.12
  • A.3 ISO/IEC 23894 Annex A A.3
1
  • A.8.2 ISO/IEC 42001 Annex A A.8.2
Cross-checksframeworks mapped in to test coverage
2
  • ibm-over-or-under-reliance Over- or under-reliance
  • ibm-over-or-under-reliance-on-ai-agents Over- or under-reliance on AI agents
1
  • GENAI.7 Human-AI Configuration
1
  • LLM09:2025 Misinformation
1
  • ASI09 Human-Agent Trust Exploitation

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Part of the Deployer AI Risk Register, an open-source resource powered by MindXO. Version 1.0, 3 July 2026. Derived from the MIT AI Risk Repository (V4, December 2025) under CC BY 4.0; an independent derivative work, not endorsed by or affiliated with MIT. Sub-risk decomposition references MITRE ATLAS™ v5.6.0 (© 2021-2026 The MITRE Corporation, reproduced and distributed with permission). ISO/IEC and EU AI Act references are by number only. License: CC BY 4.0. Full attribution and licensing.