Who Controls, Who Suffers and Who Counts? Rethinking Accountability in AI-Driven One Health
DOI:
https://doi.org/10.68903/vjta.2026.v07i02.02Keywords:
One Health, AI accountability, control-impact mismatch, cross-species ethics, moral responsibilityAbstract
Artificial intelligence (AI) systems are now embedded across One Health programmes; predicting zoonotic disease, tracking antimicrobial resistance and monitoring ecosystems. Yet governance frameworks remain inadequate in two specific and underexplored ways. First, there is a structural mismatch between those who hold control over AI systems and those who bear the consequences of their deployment. Developers who shape system behaviour never witness its real-world effects. Policymakers who authorise deployment lack the technical knowledge to assess risk. Scientists who identify failures hold no power to prevent them. This is not simply the well-known many hands problem. It is a deeper asymmetry that existing accountability frameworks do not address. Second, despite One Health’s explicit normative commitment to treating human, animal and environmental health as jointly significant, every major AI governance instrument in this domain, including the EU AI Act and the UNESCO Recommendation, remains exclusively focused on human welfare. This is an internal contradiction within One Health governance that has received almost no scholarly attention. This article proposes a Layered Relational Accountability model that directly addresses both gaps: redistributing obligations according to real capacity rather than assumed agency and embedding cross-domain moral assessment into governance processes.
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Copyright (c) 2026 Anshu Kumar (Author)
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