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The AI Risk Repository
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This page is mobile-friendly but please access on a non-mobile device for the best user experience.
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A comprehensive living database of over 700 AI risks categorized by their cause and risk domain.
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Read paper
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View website
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Watch video
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Updated: June 2024
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Contents
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A guide to the tabs in this sheet.
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Causal Taxonomy of AI Risks v0.1
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The Causal Taxonomy of AI Risks, adapted from Yampolskiy (2016), classifies risks by its causal factors (1) entity (human, AI), (2) intentionality (intentional, unintentional), and (3) timing (pre-deployment, post-deployment).
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Domain Taxonomy of AI Risks v0.1
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The Domain Taxonomy of AI Risks adapted from Weidinger (2022) classifies risks into 7 AI risk domains: (1) Discrimination & Toxicity, (2) Privacy & Security, (3) Misinformation, (4) Malicious Actors & Misuse, (5) Human-Computer Interaction, (6) Socioeconomic & Environmental, and (7) AI System Safety, Failures, & Limitations. These are further divided into 23 subdomains.
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AI Risk Database
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Our living database of risks.
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AI Risk Database explainer
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An explainer for our database of 777 risks extracted from 43 documents, categorised with the two taxonomies discussed above. You can also watch a video.
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Causal Taxonomy statistics
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See how risks are classified by the Causal Factors Taxonomy
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Domain Taxonomy statistics
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See how risks and paper are classified by the Causal Factors Taxonomy
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Causal x Domain Taxonomy comparison
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See how risks are catagorised across both taxonomies
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Included resources
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A list of all documents included in the database
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Resources being considered
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A list of all documents in consideration for future inclusion
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>>>Create your personal copy of this database<<<
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Feedback/Contact us
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πŸ’¬ Use this form to offer feedback, and suggest resources or risks to add
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πŸ“§ Email: pslat[at]mit.edu
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πŸ“„ Cite as: Slattery, P., Saeri, A. K., Grundy, E. A. C., Graham, J., Noetel, M., Uuk, R., Dao, J., Pour, S., Casper, S., & Thompson, N. (2024). A systematic evidence review and common frame of reference for the risks from artificial intelligence. http://doi.org/10.13140/RG.2.2.28850.00968