As the research and adoption of artificial intelligence continue to progress, the risks associated with using AI also increase. A team of researchers from MIT and other institutions have developed the AI Risk Repository to assist organizations in navigating the complexities of AI risks. The repository contains a database of over 700 documented risks that are categorized based on their causes and into seven distinct domains.
One of the challenges faced by the researchers in developing the AI Risk Repository was the uncoordinated efforts to document and classify AI risks. Existing classifications were fragmented and incomplete, leading to the need for a more comprehensive approach. The repository aims to consolidate information from various sources and provide organizations with a cohesive overview of AI risks.
The AI Risk Repository is designed to be a dynamic and practical resource for organizations across different sectors. It serves as a valuable checklist for risk assessment and mitigation for organizations developing or deploying AI systems. By identifying potential risks related to discrimination, bias, privacy, security, and other domains, organizations can take specific actions to address these risks effectively.
The research team behind the AI Risk Repository plans to regularly update the database with new risks, research findings, and emerging trends. This ensures that the repository remains relevant and up-to-date for organizations seeking to assess and mitigate AI risks. By adding new risks, documents, and seeking expert reviews, the repository will continue to evolve and provide useful information for organizations.
In addition to being a practical tool for organizations, the AI Risk Repository also holds value for AI risk researchers. The database and taxonomies provided by the repository offer a structured framework for synthesizing information, identifying research gaps, and guiding future investigations. This allows researchers to build on the foundation provided by the repository and conduct more specific and in-depth work on AI risks.
The research team plans to use the AI Risk Repository as a foundation for the next phase of their own research. By identifying gaps or imbalances in how risks are being addressed by organizations, the team aims to ensure that AI risks are being adequately mitigated. The repository will continue to be updated as the AI risk landscape evolves, making it a valuable resource for researchers, policymakers, and industry professionals working on AI risks and risk mitigation.
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