Artificial Intelligence Policy Tracker

MIT AI Risk Repository

Browse AI risks

8 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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8 entries

  1. 46.02.02 · Risk Sub-Category

    Financial and Economic Damage

    Propaganda - Extremist schemes

  2. "The distortion of the information ecosystem, including the spread of misinformation, fake news, and other forms of deceptive content [28], is categorized as “Information Manipulation.”"

    From GenAI against humanity: nefarious applications of generative artificial intelligence and large language models (Ferrara2023)

  3. 46.03.01 · Risk Sub-Category

    Information Manipulation

    Deception - Information control

  4. 46.03.02 · Risk Sub-Category

    Information Manipulation

    Propaganda - Influence campaigns

  5. 46.03.03 · Risk Sub-Category

    Information Manipulation

    Dishonesty - Information disorder

  6. "Lastly, broader harms that can impact communities, societal structures, and critical infrastructures, including threats to democratic processes, social cohesion, and technological systems, are captured under “Societal, Socio-technical, and Infrastructural Damage.”"

    From GenAI against humanity: nefarious applications of generative artificial intelligence and large language models (Ferrara2023)

  7. 46.04.02 · Risk Sub-Category

    Socio-technical and Infrastructural

    Propaganda - Synthetic realities

  8. 46.04.03 · Risk Sub-Category

    Socio-technical and Infrastructural

    Dishonesty - Targeted surveillance

Disclaimer: informational only, not legal advice. Verify every claim against the linked official sources and consult a qualified lawyer before acting.

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.