{"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":"49.03.02","slug":"global-ai-divide","quick_ref":"Bengio2024","paper_title":"International Scientific Report on the Safety of Advanced AI","level":"Risk Sub-Category","risk_category":"Systemic Risks ","risk_subcategory":"Global AI Divide ","description":"\"General- purpose AI research and development is currently concentrated in a few Western countries and China. This ‘AI Divide’ is multicausal, but in part related to limited access to computing power in low- income countries. Access to large and expensive quantities of computing power has become a prerequisite for developing advanced general- purpose AI. This has led to a growing dominance of large technology companies in general- purpose AI development. The AI R&D divide often overlaps with existing global socioeconomic disparities, potentially exacerbating them.\"","entity":"Other","intent":"Unintentional","timing":"Other","domain":6,"subdomain":"6.1","url":"https://aipolicytracker.org/ai-risk/risks/global-ai-divide"},{"ev_id":"49.03.03","slug":"market-concentration-risks-and-single-points-of-failure","quick_ref":"Bengio2024","paper_title":"International Scientific Report on the Safety of Advanced AI","level":"Risk Sub-Category","risk_category":"Systemic Risks ","risk_subcategory":"Market concentration risks and single points of failure","description":"\"Market power is concentrated among a few companies that are the only ones able to build the leading general- purpose AI models. Widespread adoption of a few general- purpose AI models and systems by critical sectors including finance, cybersecurity, and defence creates systemic risk because any flaws, vulnerabilities, bugs, or inherent biases in the dominant general- purpose AI models and systems could cause simultaneous failures and disruptions on a broad scale across these interdependent sectors.\"","entity":"Human","intent":"Other","timing":"Post-deployment","domain":6,"subdomain":"6.1","url":"https://aipolicytracker.org/ai-risk/risks/market-concentration-risks-and-single-points-of-failure"}]}