{"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":"2026-11-12"}
{"rows":[{"ev_id":"72.03.02","slug":"impact-on-financial-stability","quick_ref":"Tse2025","paper_title":"Frontier AI Risk Management Framework (v1.0)","level":"Risk Sub-Category","risk_category":"Accident Risks ","risk_subcategory":"Impact on Financial Stability","description":"\"The integration of general-purpose AI into high-frequency trading, market-making, or systemic risk management could exacerbate systemic risk by exhibiting unexpected behavioral patterns during market stress. Moreover, the concentration of a few homogeneous foundation models across financial institutions may foster correlated decision-making and herd-following behaviors. The widespread adoption of AI agents could also amplify volatility through emergent phenomena from multi-agent interactions.23 All of these could precipitate a cascading global-scale financial system instability, with potentia","entity":"Other","intent":"Unintentional","timing":"Post-deployment","domain":7,"subdomain":"7.6","url":"https://aipolicytracker.org/ai-risk/risks/impact-on-financial-stability"},{"ev_id":"72.05.13","slug":"multi-agent-collaboration-capability","quick_ref":"Tse2025","paper_title":"Frontier AI Risk Management Framework (v1.0)","level":"Risk Sub-Category","risk_category":"Model Capabilities ","risk_subcategory":"Multi-agent collaboration capability","description":"\"Multiple autonomous AI agents able to establish collaborative relationships through explicit communication or implicit behavioral consistency, forming decentralized decision networks, jointly executing complex tasks, achieving goals difficult for individual agents to complete, and able to dynamically adjust role divisions to adapt to changing environments.\"","entity":"AI","intent":"Intentional","timing":"Post-deployment","domain":7,"subdomain":"7.6","url":"https://aipolicytracker.org/ai-risk/risks/multi-agent-collaboration-capability"},{"ev_id":"72.06.05","slug":"multi-agent-collusion-propensity","quick_ref":"Tse2025","paper_title":"Frontier AI Risk Management Framework (v1.0)","level":"Risk Sub-Category","risk_category":"Model Propensities","risk_subcategory":"Multi-agent collusion propensity:","description":"\"Multiple agents tend to coordinate actions through covert means to maximize common interests (possibly harming third-party interests or evading regulation), even if individual agents are designed with safety constraints, their collusive behavior may still trigger systemic risks such as market manipulation or cascading failures that are difficult to detect and mitigate, and may develop specialized communication protocols to avoid monitoring.\"","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":7,"subdomain":"7.6","url":"https://aipolicytracker.org/ai-risk/risks/multi-agent-collusion-propensity"}]}