{"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":"2026-09-27"}
{"rows":[{"ev_id":"14.08.00","slug":"technological-maturity","quick_ref":"Steimers2022","paper_title":"Sources of Risk of AI Systems","level":"Risk Category","risk_category":"Technological Maturity","risk_subcategory":null,"description":"\"The technological maturity level describes how mature and error-free a certain technology is in a certain application context. If new technologies with a lower level of maturity are used in the development of the AI system, they may contain risks that are still unknown or difficult to assess.Mature technologies, on the other hand, usually have a greater variety of empirical data available, which means that risks can be identified and assessed more easily. However, with mature technologies, there is a risk that risk awareness decreases over time\"","entity":"Other","intent":"Unintentional","timing":"Other","domain":6,"subdomain":"6.4","url":"https://aipolicytracker.org/ai-risk/risks/technological-maturity"}]}