Is regulatory science ready for artificial intelligence?
Thomas Härtung, Maurice Whelan, Weida Tong, Robert M. Califf
Abstract
Trust is key in AI for regulatory science, but its definition is debated. If AI models use different features yet perform similarly, which should be trusted? If scientific theories must be testable, how critical is explainability? At the Global Summit on Regulatory Science (GSRS24), regulators agreed that successful AI adoption requires ongoing dialogue, adaptability, and AI-trained personnel to harness its potential for regulatory responsibilities in the evolving 21st-century landscape.
Topics & Concepts
AdaptabilitySummitKey (lock)Regulatory scienceEngineering ethicsComputer scienceArtificial intelligencePolitical scienceKnowledge managementManagement scienceEngineeringManagementComputer securityEconomicsBiologyPhysical geographyEcologyGeographyLaw, AI, and Intellectual PropertyBiomedical Ethics and RegulationEthics in Clinical Research