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/

5 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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5 entries

16.03.00 · Risk Category

Risk area 3: Misinformation Harms

"These risks arise from the LM outputting false, misleading, nonsensical or poor quality information, without malicious intent of the user. (The deliberate generation of "disinformation", false information that is intended to mislead, is discussed in the section on Malicious Uses.) Resulting harms range from unintentionally misinforming or deceiving a person, to causing material harm, and amplifying the erosion of societal distrust in shared information. Several risks listed here are well-documented in current large-scale LMs as well as in other language technologies"

From Taxonomy of Risks posed by Language Models (Weidinger2022)

Domain 3 3.0 AI Unintentional Post-deployment
17.03.00 · Risk Category

Misinformation Harms

"Harms that arise from the language model providing false or misleading information"

From Ethical and social risks of harm from language models (Weidinger2021)

Domain 3 3.0 AI Other Post-deployment
18.02.00 · Risk Category

Misinformation Harms

"AI systems generating and facilitating the spread of inaccurate or misleading information that causes people to develop false beliefs"

From Sociotechnical Safety Evaluation of Generative AI Systems (Weidinger2023)

Domain 3 3.0 AI Other Post-deployment
24.11.00 · Risk Category

Misinformation risks

"The rapid integration of AI systems with advanced capabilities, such as greater autonomy, content generation, memorisation and planning skills (see Chapter 4) into personalised assistants also raises new and more specific challenges related to misinformation, disinformation and the broader integrity of our information environment. "

From The Ethics of Advanced AI Assistants (Gabriel2024)

Domain 3 3.0 Other Other Other
58.07.06 · Risk Sub-Category

Societal and Cultural

Historical revisionism

"Historical revisionism - Deliberate or unintentional reinterpretation of established/orthodox historical events or accounts held by societies, communities, academics."

From A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

Domain 3 3.0 Other Other Other

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