MIT Researchers Release Public Repository of AI Risks

To address the growing risks associated with using AI, MIT and other organizations have released a comprehensive AI Risk Repository. It is a living database that has over 700 AI risks categorized by cause and risk domain.

The repository aims to help decision-makers in government, research, and industry assess the evolving risks of AI. “What we really wanted to do was to have a neutral and comprehensive database, and by neutral, I mean to take everything as presented and be very transparent about that,” says the database’s lead author, Peter Slattery, a postdoctoral associate at MIT FutureTech.

To tackle this challenge, the repository consolidates information from 43 existing taxonomies, including peer-reviewed articles, preprints, conference papers, and reports. This process has resulted in a database of more than 700 unique risks.

The AI Risk Repository is publicly accessible, and organizations can download it for their own use. The research team plans to regularly update the database with new risks, research findings, and emerging trends. 

Apart from organizational usage, the AI Risk Repository also proves to be a valuable resource for AI risk researchers. The research team states that the database and taxonomies provide a structured framework for synthesizing information, identifying research gaps, and guiding future investigations.

Further, the research team plans to use the AI Risk Repository as a foundation for the next phase of their own research. In addition, the team is driven to keep the Risk Repository updated and relevant, maintaining its usefulness for researchers, policymakers, and industry professionals working on AI risks and risk mitigation.

“We intend this to be a living database, the start of something. We’re very keen to get feedback on this,” Slattery says. “We haven’t put this out saying, ‘We’ve really figured it out, and everything we’ve done is going to be perfect.’”