Transforming Chemical Safety Policy in the AI Era: A Seven-Action Strategy for the Five Chemical Safety Acts Under the Ministry of Climate, Energy, and Environment

Abstract

Chemical safety in the Republic of Korea is governed by five acts falling under the purview of the Ministry of Climate, Energy, and Environment (MCEE): the Act on Registration and Evaluation of Chemicals (K-REACH Act), the Chemicals Control Act (CCA), the Environmental Health Act, the Environmental Damage Relief Act, and the Consumer Chemical Products and Biocides Safety Act.These five acts manage substantial datasets but operate on largely independent data systems, classification schemes, and identifiers, which limits cross-act risk prediction and timely policy responses.Advances in artificial intelligence (AI) and knowledge graph technologies suggest a possible paradigm shift, but realizing this potential calls for a redesign of data infrastructure and institutional frameworks tailored to the five-act structure.Drawing on international best practices, including the European Union (EU) One Substance One Assessment (OSOA) package, the EU Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) regulation, the United States Toxic Substances Control Act (TSCA), Data Catalog Vocabulary-Application Profile (DCAT-AP) metadata standards, and ontology-and knowledge graph-based chemical safety studies, as well as on the structural lessons of past data-integration failures such as the 9/11 information silos, a seven-action strategy is proposed: (1) Designating high-value chemical-safety datasets across the five acts; (2) Redesigning data collection around policy questions; (3) Adopting DCAT-based metadata standards; (4) Developing a chemical-safety domain ontology with cross-act bridges anchored by a common chemical identifier; (5) Transforming incident reports into knowledge graphs; (6) Building AI-based early warning and prioritization systems; and(7) Institutionalizing explainable AI.The seven actions form a logical pipeline from data through metadata, ontology, knowledge graph, AI, and explainability, and are intended to be pursued in a stepwise manner.Realizing this transformation will likely require coordination across the five acts within MCEE, legal safeguards, and sustained investment in data curation and explainable AI.