Physical safety harm and accidents
Failures of AI in safety-critical systems, critical infrastructure, or embodied/robotic settings cause physical injury, accidents, or property damage.
- Risk family
- Model & system behaviour
- MIT domain
- 7. AI System Safety, Failures, & Limitations
- MIT subdomain
- X.1 > Excluded
- AI type
- GPAI, Agentic, Classical_ML
- Scope
- System
- Source standard
- MIT AI Risk Repository v4
Provenance
49 entries across 25 papers
- Abercrombie2024A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms58.02.00 58.02.01 58.02.03 58.02.04 58.07.05 58.08.01
- AIVerify2023Summary Report: Binary Classification Model for Credit Risk26.04.00
- Allianz2018The Rise of Artificial Intelligence - Future Outlooks and Emerging Risks41.03.00 41.03.02
- Cunha2023Navigating the Landscape of AI Ethics and Responsibility03.01.00
- Everitt2018AGI Safety Literature Review51.05.00 51.10.00
- Gabriel2024The Ethics of Advanced AI Assistants24.01.00 24.01.01 24.10.04
- Ghosh2024AILUMINATE: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons57.01.00 57.02.05
- Gipiškis2024Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems62.07.03 62.07.04 62.30.01 62.30.03
- Hendrycks2023An Overview of Catastrophic AI Risks22.03.00 22.03.01 22.03.02
- Kilian2023Examining the differential risk from high-level artificial intelligence and the question of control07.02.00
- Li2025A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents66.11.00 66.11.02 66.11.04 66.11.05
- Maham2023Governing General Purpose AI: A Comprehensive Map of Unreliability, Misuse and Systemic Risks52.01.03
- Meek2016Managing the ethical and risk implications of rapid advances in artificial intelligence: A literature review09.05.01 09.05.02
- Paes2023Social Impacts of Artificial Intelligence and Mitigation Recommendations: An Exploratory Study10.02.00
- Perlo2025Embodied AI: Emerging Risks and Opportunities for Policy Action70.01.00 70.01.02
- Saghiri2022A Survey of Artificial Intelligence Challenges: Analyzing the Definitions, Relationships, and Evolutions39.10.00
- Schnitzer2024AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks59.01.00
- Steimers2022Sources of Risk of AI Systems14.06.00
- Tan2022The Risks of Machine Learning Systems15.02.01
- Tang2025Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy71.01.04 71.03.02
- Teixeira2022An Exploratory Diagnosis of Artificial Intelligence Risks for a Responsible Governance42.04.00 42.23.00
- Tse2025Frontier AI Risk Management Framework (v1.0)72.01.03 72.03.00 72.03.01
- Weidinger2021Ethical and social risks of harm from language models17.06.04
- Weidinger2022Taxonomy of Risks posed by Language Models16.06.04
- Weidinger2023Sociotechnical Safety Evaluation of Generative AI Systems18.06.01
Ev IDs of the entries consolidated into this risk in the MIT AI Risk Repository (V4); the source sheet row appears on hover.
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.
1- A.10 ISO/IEC 23894 Annex A A.10
2- A.5.4 ISO/IEC 42001 Annex A A.5.4
- A.6.2.4 ISO/IEC 42001 Annex A A.6.2.4
More in Model & system behaviour
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.