{"attribution":{"source":"MIT AI Risk Repository, Domain Taxonomy of AI Risks v1 (MIT AI Risk Initiative)","license":"CC BY 4.0","license_url":"https://creativecommons.org/licenses/by/4.0/","citation":"Slattery, P., Saeri, A. K., Grundy, E. A. C., Graham, J., Noetel, M., Uuk, R., Dao, J., Pour, S., Casper, S., & Thompson, N. (2025). The AI Risk Repository: A comprehensive meta-review, database, and taxonomy of risks from artificial intelligence. arXiv:2408.12622."},"exported_at":"2026-09-12"}
{"rows":[{"ev_id":"66.03.02","quick_ref":"Li2025","paper_title":"A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents","level":"Risk Sub-Category","risk_category":"Misinformation Harms ","risk_subcategory":"Pollution of information ecosystems","description":"\"Contaminating publicly available information with false or inaccurate information (i.e., the generative tool's output is disseminated beyond the end user)\"","entity":"Other","intent":"Other","timing":"Post-deployment","domain":3,"subdomain":"3.2"},{"ev_id":"66.03.03","quick_ref":"Li2025","paper_title":"A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents","level":"Risk Sub-Category","risk_category":"Misinformation Harms ","risk_subcategory":"Erosion of trust in public information","description":"\"Eroding trust in public information and knowledge\"","entity":"Other","intent":"Other","timing":"Other","domain":3,"subdomain":"3.2"},{"ev_id":"66.04.01","quick_ref":"Li2025","paper_title":"A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents","level":"Risk Sub-Category","risk_category":"Societal and Cultural","risk_subcategory":"Overburdening ecosystems","description":"\"Pollution of a space/ecosystem that is expected to be free of AI involvement/influence (e.g., creative material submission portals, job applications)\"","entity":"Other","intent":"Other","timing":"Other","domain":3,"subdomain":"3.2"}]}