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Beyond the principle-practice gap: Responsible AI as situated epistemic and ethical practice

This paper challenges the common framing of the gap between AI ethics principles and practice as a mere implementation or compliance deficit. Based on interviews with actors in AI-enabled anti-trafficking systems, it argues that ethical concerns are shaped by institutional and professional contexts, and that epistemic choices are intertwined with ethical judgments. The authors propose a model of four moments—perception, judgment, situated action, and socio-technical materialization—through which concerns become actionable or are deferred. They conclude that responsible AI governance requires epistemic infrastructures to make affected communities' knowledge receivable in design.