{"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":"31.01.00","quick_ref":"EPIC2023","paper_title":"Generating Harms - Generative AI's impact and paths forwards","level":"Risk Category","risk_category":"Information Manipulation","risk_subcategory":null,"description":"\"generative AI tools can and will be used to propagate content that is false, misleading, biased, inflammatory, or dangerous. As generative AI tools grow more sophisticated, it will be quicker, cheaper, and easier to produce this content—and existing harmful content can serve as the foundation to produce more\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":4,"subdomain":"4.1"},{"ev_id":"31.01.01","quick_ref":"EPIC2023","paper_title":"Generating Harms - Generative AI's impact and paths forwards","level":"Risk Sub-Category","risk_category":"Information Manipulation","risk_subcategory":"Scams","description":"\"Bad actors can also use generative AI tools to produce adaptable content designed to support a campaign, political agenda, or hateful position and spread that information quickly and inexpensively across many platforms. This rapid spread of false or misleading content—AI-facilitated disinformation—can also create a cyclical effect for generative AI: when a high volume of disinformation is pumped into the digital ecosystem and more generative systems are trained on that information via reinforcement learning methods, for example, false or misleading inputs can create increasingly incorrect out","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":4,"subdomain":"4.3"},{"ev_id":"31.01.02","quick_ref":"EPIC2023","paper_title":"Generating Harms - Generative AI's impact and paths forwards","level":"Risk Sub-Category","risk_category":"Information Manipulation","risk_subcategory":"Disinformation","description":"\"Bad actors can also use generative AI tools to produce adaptable content designed to support a campaign, political agenda, or hateful position and spread that information quickly and inexpensively across many platforms.\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":4,"subdomain":"4.1"},{"ev_id":"31.01.04","quick_ref":"EPIC2023","paper_title":"Generating Harms - Generative AI's impact and paths forwards","level":"Risk Sub-Category","risk_category":"Information Manipulation","risk_subcategory":"Security","description":"\"Though chatbots cannot (yet) develop their own novel malware from scratch, hackers could soon potentially use the coding abilities of large language models like ChatGPT to create malware that can then be minutely adjusted for maximum reach and effect, essentially allowing more novice hackers to become a serious security risk\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":4,"subdomain":"4.2"},{"ev_id":"31.02.00","quick_ref":"EPIC2023","paper_title":"Generating Harms - Generative AI's impact and paths forwards","level":"Risk Category","risk_category":"Harassment, Impersonation, and Extortion","risk_subcategory":null,"description":"\"Deepfakes and other AI-generated content can be used to facilitate or exacerbate many of the harms listed throughout this report, but this section focuses on one subset: intentional, targeted abuse of individuals.\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":4,"subdomain":"4.3"},{"ev_id":"31.02.01","quick_ref":"EPIC2023","paper_title":"Generating Harms - Generative AI's impact and paths forwards","level":"Risk Sub-Category","risk_category":"Harassment, Impersonation, and Extortion","risk_subcategory":"Malicious intent","description":"\"A frequent malicious use case of generative AI to harm, humiliate, or sexualize another person involves generating deepfakes of nonconsensual sexual imagery or videos.\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":4,"subdomain":"4.3"},{"ev_id":"31.02.02","quick_ref":"EPIC2023","paper_title":"Generating Harms - Generative AI's impact and paths forwards","level":"Risk Sub-Category","risk_category":"Harassment, Impersonation, and Extortion","risk_subcategory":"Privacy and consent","description":"\"Even when a victim of targeted, AIgenerated harms successfully identifies a deepfake creator with malicious intent, they may still struggle to redress many harms because the generated image or video isn’t the victim, but instead a composite image or video using aspects of multiple sources to create a believable, yet fictional, scene. At their core, these AI-generated images and videos circumvent traditional notions of privacy and consent: because they rely on public images and videos, like those posted on social media websites, they often don’t rely on any private information.\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":4,"subdomain":"4.3"},{"ev_id":"31.02.03","quick_ref":"EPIC2023","paper_title":"Generating Harms - Generative AI's impact and paths forwards","level":"Risk Sub-Category","risk_category":"Harassment, Impersonation, and Extortion","risk_subcategory":"Believability","description":"Deepfakes can impose real social injuries on their subjects when they are circulated to viewers who think they are real. Even when a deepfake is debunked, it can have a persistent negative impact on how others view the subject of the deepfake.3","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":4,"subdomain":"4.3"},{"ev_id":"31.04.00","quick_ref":"EPIC2023","paper_title":"Generating Harms - Generative AI's impact and paths forwards","level":"Risk Category","risk_category":"Data Security Risk","risk_subcategory":null,"description":"\"Just as every other type of individual and organization has explored possible use cases for generative AI products, so too have malicious actors. This could take the form of facilitating or scaling up existing threat methods, for example drafting actual malware code,87 business email compromise attempts,88 and phishing attempts.89 This could also take the form of new types of threat methods, for example mining information fed into the AI’s learning model dataset90 or poisoning the learning model data set with strategically bad data.91 We should also expect that there will be new attack vector","entity":"Human","intent":"Intentional","timing":"Other","domain":4,"subdomain":"4.3"}]}