{"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":"26.01.00","quick_ref":"AIVerify2023","paper_title":"Summary Report: Binary Classification Model for Credit Risk","level":"Risk Category","risk_category":"Transparency","risk_subcategory":null,"description":"\"Ability to provide responsible disclosure to those affected by AI systems to understand the outcome\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":null,"subdomain":null},{"ev_id":"26.02.00","quick_ref":"AIVerify2023","paper_title":"Summary Report: Binary Classification Model for Credit Risk","level":"Risk Category","risk_category":"Explainability","risk_subcategory":null,"description":"\"Ability to assess the factors that led to the AI system's decision, its overall behaviour, outcomes, and implications\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":null,"subdomain":null},{"ev_id":"26.03.00","quick_ref":"AIVerify2023","paper_title":"Summary Report: Binary Classification Model for Credit Risk","level":"Risk Category","risk_category":"Repeatability / Reproducibility","risk_subcategory":null,"description":"\"The ability of a system to consistently perform its required functions under stated conditions for a specific period of time, and for an independent party to produce the same results given similar inputs\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":null,"subdomain":null},{"ev_id":"26.04.00","quick_ref":"AIVerify2023","paper_title":"Summary Report: Binary Classification Model for Credit Risk","level":"Risk Category","risk_category":"Safety","risk_subcategory":null,"description":"\"AI should not result in harm to humans (particularly physical harm), and measures should be put in place to mitigate harm\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":null,"subdomain":null},{"ev_id":"26.05.00","quick_ref":"AIVerify2023","paper_title":"Summary Report: Binary Classification Model for Credit Risk","level":"Risk Category","risk_category":"Security","risk_subcategory":null,"description":"\"AI security is the protection of AI systems, their data, and the associated infrastructure from unauthorised access, disclosure, modification, destruction, or disruption. AI systems that can maintain confidentiality, integrity, and availability through protection mechanisms that prevent unauthorized access and use may be said to be secure.\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":null,"subdomain":null},{"ev_id":"26.06.00","quick_ref":"AIVerify2023","paper_title":"Summary Report: Binary Classification Model for Credit Risk","level":"Risk Category","risk_category":"Robustness","risk_subcategory":null,"description":"\"AI system should be resilient against attacks and attempts at manipulation by third party malicious actors, and can still function despite unexpected input\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":null,"subdomain":null},{"ev_id":"26.07.00","quick_ref":"AIVerify2023","paper_title":"Summary Report: Binary Classification Model for Credit Risk","level":"Risk Category","risk_category":"Fairness","risk_subcategory":null,"description":"\"AI should not result in unintended and inappropriate discrimination against individuals or groups\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":null,"subdomain":null},{"ev_id":"26.08.00","quick_ref":"AIVerify2023","paper_title":"Summary Report: Binary Classification Model for Credit Risk","level":"Risk Category","risk_category":"Data Governance","risk_subcategory":null,"description":"\"Governing data used in AI systems, including putting in place good governance practices for data quality, lineage, and compliance\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":null,"subdomain":null},{"ev_id":"26.09.00","quick_ref":"AIVerify2023","paper_title":"Summary Report: Binary Classification Model for Credit Risk","level":"Risk Category","risk_category":"Accountability","risk_subcategory":null,"description":"\"AI systems should have organisational structures and actors accountable for the proper functioning of AI systems\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":null,"subdomain":null},{"ev_id":"26.10.00","quick_ref":"AIVerify2023","paper_title":"Summary Report: Binary Classification Model for Credit Risk","level":"Risk Category","risk_category":"Human Agency & Oversight","risk_subcategory":null,"description":"\"Ability to implement appropriate oversight and control measures with humans-in-the-loop at the appropriate juncture\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":null,"subdomain":null},{"ev_id":"26.11.00","quick_ref":"AIVerify2023","paper_title":"Summary Report: Binary Classification Model for Credit Risk","level":"Risk Category","risk_category":"Inclusive Growth, Societal & Environmental Well-being","risk_subcategory":null,"description":"\"This Principle highlights the potential for trustworthy AI to contribute to overall growth and prosperity for all – individuals, society, and the planet – and advance global development objectives\"","entity":"Not coded","intent":"Not coded","timing":"Not coded","domain":null,"subdomain":null}]}