AI and Epidemic Response: Between Intelligence and Illusion
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Abstract
This paper examines how Artificial Intelligence (AI) evolved during the COVID-19 pandemic from a predictive tool into a potential partner in epidemic response. While AI was widely promoted as a guide for decision-making under uncertainty, real-world experience exposed a persistent gap between algorithmic capability and institutional use. Many predictive models struggled to adapt to rapidly changing human behavior and social conditions, demonstrating that epidemics are not only medical crises but also governance, coordination, and logistics challenges. This paper argues for a shift toward Responsible AI that prioritizes decision support over prediction and is embedded within public health operations. It introduces the concept of “expiration logic” to ensure that emergency AI systems remain accountable and do not outlast their legitimate use. Ultimately, AI’s value lies in strengthening human judgment and institutional resilience rather than replacing them.
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Copyright (c) 2025 Tsagkarliotis I.
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