What is the MIT AI Risk Repository?

A living database of AI risks extracted from 74 frameworks, taxonomies and papers, classified by a causal taxonomy (entity, intent, timing) and a domain taxonomy (7 domains, 24 subdomains). Published by the MIT AI Risk Initiative under CC BY 4.0.

Can I download the filtered risk list?

Yes. Apply filters and use Export CSV or Export JSON; the file carries the source, licence and citation so it can be reused with attribution.

MIT AI Risk Repository

Browse AI risks

Name: MIT AI Risk Repository: AI Risk Database (browseable copy)
Creator: MIT AI Risk Initiative
License: https://creativecommons.org/licenses/by/4.0/

107 risk entries extracted from 74 frameworks, coded by domain, subdomain, causal entity, intent and timing. Filter, then export the current selection with its licence and citation attached.

Export CSV Export JSON

107 entries · page 3 of 3

66.07.06 · Risk Sub-Category

Psychological

Addiction

"Emotional or material dependence on technology or a technology system"

From A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents (Li2025)

Domain 5 5.2 Other Other Post-deployment
67.04.00 · Risk Category

Loss of control

-

"Humans may increasingly hand over control of important decisions to AI systems, due to economic and geopolitical incentives. Some experts are concerned that future advanced AI systems will seek to increase their own influence and reduce human control, with potentially catastrophic consequences - although this is contested."

From Capabilities and Risks from Frontier AI (DSIT2023)

Domain 5 5.2 Other Other Post-deployment
67.04.01 · Risk Sub-Category

Loss of control

Humans might increasingly hand over control to misaligned AI systems

"Organisations around the world are already deploying misaligned AI systems that are causing harm in unexpected ways.250 Recommendation algorithms increase the consumption of extremist content.251 Medical algorithms have been known to misdiagnose US patients,252 and recommend incorrect prescriptions.253 Still, we hand over more control to them, often because they are still as - or more - effective than human decision making, or because they are cheaper."

From Capabilities and Risks from Frontier AI (DSIT2023)

Domain 5 5.2 Human Unintentional Other
68.04.00 · Risk Category

Gradual loss of control

"Gradual or accumulative loss of control risks can be described as risks resulting from the accumulation of less severe disruptions that gradually weakens systemic resilience until a critical event triggers a catastrophe [12], [127]."

From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

Domain 5 5.2 Other Unintentional Other
68.04.00a · Additional evidence

Gradual loss of control

"Risk dimensions • Intent: Unintentional • Competency: Variable • Entity: Variable • Polarity: Multi-agent • Linearity: Non-linear • Reach: Internalized • Order: Variable"

From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

Domain 5 5.2 Other Unintentional Other
72.02.00 · Risk Category

Loss of Control Risks

"Risks associated with scenarios in which one or more general-purpose AI systems come to operate outside of anyone's control, with no clear path to regaining control. This includes both passive loss of control (gradual reduction in human oversight) and active loss of control (AI systems actively undermining human control)"

From Frontier AI Risk Management Framework (v1.0) (Tse2025)

Domain 5 5.2 AI Other Post-deployment
72.02.01 · Risk Sub-Category

Loss of Control Risks

Passive loss of control

"...where humans gradually stop exercising meaningful oversight due to automation bias, the AI systems' inherent complexity, or competitive pressures"

From Frontier AI Risk Management Framework (v1.0) (Tse2025)

Domain 5 5.2 Other Unintentional Other

Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.