  We present a comprehensive AI risk taxonomy derived from eight government
policies from the European Union, United States, and China and 16 company
policies worldwide, making a significant step towards establishing a unified
language for generative AI safety evaluation. We identify 314 unique risk
categories organized into a four-tiered taxonomy. At the highest level, this
taxonomy encompasses System & Operational Risks, Content Safety Risks, Societal
Risks, and Legal & Rights Risks. The taxonomy establishes connections between
various descriptions and approaches to risk, highlighting the overlaps and
discrepancies between public and private sector conceptions of risk. By
providing this unified framework, we aim to advance AI safety through
information sharing across sectors and the promotion of best practices in risk
mitigation for generative AI models and systems.
