DIGITAL AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES FOR ENHANCING THE ENFORCEMENT OF DRUG PREVENTION AND SUPPRESSION POLICIES: LESSONS FROM THAILAND, SINGAPORE, AND SOUTH KOREA

Abstract

This academic article examines and analyzes the application of digital technologies and artificial intelligence (AI) in the enforcement of drug prevention and suppression policies, through a comparative study of three countries: Thailand, the Republic of Singapore, and the Republic of Korea. The study employs systematic literature review and document analysis drawing from policy reports, academic databases, and regional publications. Findings reveal that all three countries have adopted digital technologies with varying degrees of intensity and focus, shaped by their distinct societal contexts and digital infrastructure capacities. Thailand concentrates on information systems for asset tracking, Telepsychiatry in correctional facilities, and the V-Care system for high-risk psychiatric patients. Singapore stands out for its robust Digital Public Infrastructure (DPI) and near-universal digital identity coverage. South Korea leads with predictive artificial intelligence through the Multi-Agent-Based Modeling (MABM) system and the Basic AI Act framework, which establishes a trustworthy AI governance model. This article proposes a Three-Dimensional Digital-AI Policy Framework (3D-DAP Framework) comprising digital infrastructure, AI-driven policy intelligence, and data governance dimensions as a pathway for enhancing drug policy enforcement in developing country contexts. Key findings indicate that the critical success factors for deploying digital technologies and AI in drug prevention and suppression encompass three principal elements: seamlessly interoperable digital infrastructure, personnel capacity for technology acceptance and utilization, and a clearly defined data governance framework.