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Short abstract

This paper examines how AI in healthcare governs not only bodies and data, but also emotions. Drawing on STS and affect theory, it argues that AI-mediated health technologies codify and circulate emotional norms by translating feeling rules into computational forms of affective regulation.

Long abstract

AI applications in the health sector increasingly operate as regulatory devices that govern not only bodies and data, but also feelings. As AI is applied in diagnostic and therapeutic practices, the management of emotions itself becomes being automated and standardized. This contribution examines how these AI devices enact new modes of governance by translating psychological concepts, societal norms and expectations of emotional behavior into technical design. Through this translation, I argue “feeling rules” (Hochschild 1979) representing prevailing expectations of appropriate emotions are recast as computational logics seeking to stabilize social order through emotional regulation. Drawing on STS and affect theory, this contribution conceptualizes AI based health applications as socio technical assemblages of affective regulation. Diagnostic algorithms categorize emotional states, while therapeutic chatbots model empathy, resilience and self care as measurable and optimizable behaviors. These systems extend governance into the emotional domain, aligning well-being and social stability with predictive analytics and automated care. Based on empirical material and a comparative perspective on Germany and Japan, the paper analyzes how AI-mediated health technologies codify and govern emotions across different sociotechnical and cultural contexts. It discusses if the promise of digitized care gives rise to new forms of emotional and affective governance, situating citizens within algorithmic regimes of feeling and broader projects of social order, technological rationality, and the governance of democratic life.