This study, presented by Lee et al., examines how the construction of an AI-enabled governance model can address public acceptance and risks during emerging public health crises. By constructing a comprehensive model called the Risk centered and AI-enabled Anti-pandemic Technology Acceptance Model (RPAA-TAM), the authors build on existing Technology Acceptance Model (TAM) literature, further integrating social influence theory and risk perception theory to better understand factors that influence public acceptance of AI in pandemic prevention. As a result, the study identifies seven key factors that influence public acceptance, including public trust, perceived benefit, perceived risk, and behavioral intention. More specifically, the research concluded that public trust in the government and its use of AI significantly influences the perceived benefit of the technologies. This benefit can then positively impact one’s attitude toward using the technology, which leads to a greater behavioral intention to use it. The study also highlighted that perceived risks such as data privacy concerns are essential in shaping one’s attitude toward using that technology, even during a crisis.