Where do these risk entries come from?

The MIT AI Risk Repository, which extracts risks from dozens of published frameworks, taxonomies and papers and codes each one by domain and subdomain, and by a causal taxonomy of entity, intent and timing. This is a browseable copy, attributed and openly licensed, not original research.

What do entity, intent and timing mean?

They are the causal coding. Entity is whether a human or the AI system is the cause; intent is whether the harm was intentional or not; timing is whether it arises before or after deployment. Together they let you separate misuse from malfunction.

Can I export the results?

Yes, any filtered set exports as CSV or JSON, and every export carries the upstream source, licence and citation with it, because attribution is a condition of the licence rather than a courtesy.

What is the MIT AI Risk Repository?

A living database of AI risks extracted from published frameworks, taxonomies and papers, classified by a causal taxonomy of entity, intent and timing and by a domain taxonomy of seven domains and 24 subdomains. It is published by the MIT AI Risk Initiative under CC BY 4.0.

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/

54 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.

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54 entries · page 2 of 2

70.03.03 · Risk Sub-Category

Economic Risks

Power concentration

"EAI deployment could accelerate the consolidation of economic and political power. Unlocking increasing returns to capital for EAI owners, EAI will decrease employers’ reliance on and responsiveness to the needs of human labor [101]."

From Embodied AI: Emerging Risks and Opportunities for Policy Action (Perlo2025)

Domain 6 6.1 AI Unintentional Post-deployment
72.04.02 · Risk Sub-Category

Systemic Risks

Market Concentration and Infrastructure Dependencies:

"Over-reliance on a limited number of dominant AI providers could create critical single points of failure across essential services. Market concentration in AI development may lead to scenarios where technical failures, cyber-attacks, or policy decisions by a few companies could simultaneously disrupt healthcare systems, financial services, transportation networks, and communication infrastructure, creating cascading failures across interconnected critical systems."

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

Domain 6 6.1 Human Unintentional Other
72.04.03 · Risk Sub-Category

Systemic Risks

Global AI Research and Development Divides:

"Asymmetric AI development capabilities between nations could exacerbate geopolitical tensions and create new forms of technological dependency. Countries lacking advanced AI capabilities may become increasingly dependent on foreign AI systems for critical functions, while AI-leading nations may gain disproportionate influence over global economic and security systems, potentially destabilizing international cooperation frameworks."

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

Domain 6 6.1 Other Unintentional Other
73.06.00 · Risk Category

Corporate power may impeded effective governance

"The increasing power and influence of large corporations may make effective governance difficult. There exists a power asymmetry between corporate entities profiting from LLMs and other social groups (e.g. civil society). State-of-the-art LLMs are developed by or in partnership with, some of the world’s largest private tech companies...This poses a risk of governance protocols related to LLMs becoming excessively favorable to tech companies, potentially leading to regulatory capture at the cost of the interests of other societal groups, particularly marginalized communities who have historica

From Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

Domain 6 6.1 Other Unintentional Other

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Frequently asked questions

Where do these risk entries come from?: The MIT AI Risk Repository, which extracts risks from dozens of published frameworks, taxonomies and papers and codes each one by domain and subdomain, and by a causal taxonomy of entity, intent and timing. This is a browseable copy, attributed and openly licensed, not original research.
What do entity, intent and timing mean?: They are the causal coding. Entity is whether a human or the AI system is the cause; intent is whether the harm was intentional or not; timing is whether it arises before or after deployment. Together they let you separate misuse from malfunction.
Can I export the results?: Yes, any filtered set exports as CSV or JSON, and every export carries the upstream source, licence and citation with it, because attribution is a condition of the licence rather than a courtesy.
What is the MIT AI Risk Repository?: A living database of AI risks extracted from published frameworks, taxonomies and papers, classified by a causal taxonomy of entity, intent and timing and by a domain taxonomy of seven domains and 24 subdomains. It is published by the MIT AI Risk Initiative under CC BY 4.0.