{"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":"2026-09-13"}
{"rows":[{"ev_id":"66.08.03","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":"Financial and Business","risk_subcategory":"Confidentiality loss","description":"\"Unauthorised sharing of sensitive, confidential information and documents such as corporate strategy and financial plans with third-parties, risking loss of market position or revenue\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":2,"subdomain":"2.1"},{"ev_id":"66.09.01","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":"Privacy and Security","risk_subcategory":"Exclusion","description":"\"The failure to provide end-users with notice and control over how their data is being used; AI exacerbates exclusion risks by training on rich personal data without consent.\"","entity":"AI","intent":"Other","timing":"Other","domain":2,"subdomain":"2.1"},{"ev_id":"66.09.03","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":"Privacy and Security","risk_subcategory":"Disclosure","description":"\"Revealing and improperly sharing data of individuals; AI creates new types of disclosure risks by inferring additional information beyond what is explicitly captured in the raw data; AI exacerbates disclosure risks through sharing personal data to train models.\"","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":2,"subdomain":"2.1"},{"ev_id":"66.09.04","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":"Privacy and Security","risk_subcategory":"Secondary use","description":"\"The use of personal data collected for one purpose for a diferent purpose without end-user consent; AI exacerbates secondary use risks by creating new AI capabilities with collected personal data, and (re)creating models from a public dataset.\"","entity":"Human","intent":"Intentional","timing":"Other","domain":2,"subdomain":"2.1"},{"ev_id":"66.09.05","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":"Privacy and Security","risk_subcategory":"Exposure","description":"\"Revealing sensitive private information that people view as deeply primordial that we have been socialized into concealing; AI creates new types of exposure risks through generative techniques that can reconstruct censored or redacted content; and through exposing inferred sensitive data, preferences, and intentions.\"","entity":"AI","intent":"Unintentional","timing":"Other","domain":2,"subdomain":"2.1"},{"ev_id":"66.09.07","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":"Privacy and Security","risk_subcategory":"Insecurity","description":"\"carelessness in protecting collected personal data from leaks and improper access due to faulty data storage and data practices\"","entity":"Human","intent":"Unintentional","timing":"Other","domain":2,"subdomain":"2.1"}]}