Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems
This work helps AI providers, policymakers, and regulators identify and mitigate systemic risks from GPAI systems, though it is incremental as it documents existing knowledge rather than proposing new methods.
The paper compiles an extensive catalog of risk sources and risk management measures for general-purpose AI systems to support global AI regulation and safety standards, identifying technical, operational, and societal risks across development stages.
There is an urgent need to identify both short and long-term risks from newly emerging types of Artificial Intelligence (AI), as well as available risk management measures. In response, and to support global efforts in regulating AI and writing safety standards, we compile an extensive catalog of risk sources and risk management measures for general-purpose AI (GPAI) systems, complete with descriptions and supporting examples where relevant. This work involves identifying technical, operational, and societal risks across model development, training, and deployment stages, as well as surveying established and experimental methods for managing these risks. To the best of our knowledge, this paper is the first of its kind to provide extensive documentation of both GPAI risk sources and risk management measures that are descriptive, self-contained and neutral with respect to any existing regulatory framework. This work intends to help AI providers, standards experts, researchers, policymakers, and regulators in identifying and mitigating systemic risks from GPAI systems. For this reason, the catalog is released under a public domain license for ease of direct use by stakeholders in AI governance and standards.