{"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":"2026-09-11"}
{"rows":[{"ev_id":"65.14.05","quick_ref":"IBM2025","paper_title":"AI Risk Atlas ","level":"Risk Sub-Category","risk_category":"Output risks (misuse) ","risk_subcategory":"Nonconsensual use","description":"\"Generative AI models might be intentionally used to imitate people through deepfakes by using video, images, audio, or other modalities without their consent.\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":4,"subdomain":"4.3"},{"ev_id":"65.23.02","quick_ref":"IBM2025","paper_title":"AI Risk Atlas ","level":"Risk Sub-Category","risk_category":"Non-technical risks (Societal impact)","risk_subcategory":"Impact on education: plagiarism ","description":"\"Easy access to high-quality generative models might result in students that use AI models to plagiarize existing work intentionally or unintentionally.\"","entity":"Human","intent":"Other","timing":"Post-deployment","domain":4,"subdomain":"4.3"},{"ev_id":"65.23.05","quick_ref":"IBM2025","paper_title":"AI Risk Atlas ","level":"Risk Sub-Category","risk_category":"Non-technical risks (Societal impact)","risk_subcategory":"Impact on education: bypassing learning ","description":"\"Easy access to high-quality generative models might result in students that use AI models to bypass the learning process.\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":4,"subdomain":"4.3"}]}