The AI Risk Repository: A Comprehensive Database for Assessing AI Risks
As the field of artificial intelligence (AI) continues to advance, so do the risks associated with its use. To address these risks, researchers from MIT and other institutions have developed the AI Risk Repository, a comprehensive database that aims to help decision-makers in government, research, and industry assess the evolving risks of AI.
Bringing Order to AI Risk Classification
While many organizations recognize the need to address AI risks, efforts to document and classify these risks have been uncoordinated, resulting in a fragmented landscape of conflicting classification systems. The AI Risk Repository seeks to solve this issue by consolidating information from 43 existing taxonomies, resulting in a database of over 700 unique risks.
The repository uses a two-dimensional classification system. First, risks are categorized based on their causes, considering factors such as the responsible entity (human or AI), intent (intentional or unintentional), and timing (pre-deployment or post-deployment). This classification helps to understand how AI risks can arise. Second, risks are classified into seven domains, including discrimination and toxicity, privacy and security, misinformation and malicious actors, and misuse.
Evaluating AI Risks for the Enterprise
The AI Risk Repository serves as a practical resource for organizations in different sectors. It provides a valuable checklist for risk assessment and mitigation for organizations developing or deploying AI systems. For example, a company developing an AI-powered hiring system can use the repository to identify potential risks related to discrimination and bias. Similarly, a company using AI for content moderation can leverage the “Misinformation” domain to understand the risks associated with AI-generated content.
While organizations will need to tailor their risk assessment and mitigation strategies to their specific contexts, having a centralized and well-structured repository like this reduces the likelihood of overlooking critical risks.
Shaping Future AI Risk Research
The AI Risk Repository also benefits AI risk researchers by providing a structured framework for synthesizing information, identifying research gaps, and guiding future investigations. Researchers can use the database and taxonomies as a foundation for more specific work, saving time and increasing oversight.
The research team behind the AI Risk Repository plans to use it as a foundation for their own future research. By identifying potential gaps or imbalances in how risks are being addressed by organizations, they can explore if there is a disproportionate focus on certain risk categories while others are being underaddressed. As the AI risk landscape evolves, the repository will be regularly updated to remain a useful resource for researchers, policymakers, and industry professionals.
In conclusion, the AI Risk Repository provides a valuable tool for understanding and managing the risks associated with AI. By consolidating and classifying hundreds of risks, it helps decision-makers in various sectors assess and mitigate the potential harms of AI systems. As AI continues to advance, this repository will play a crucial role in shaping future research and ensuring responsible AI development.