Abstract Contemporary AI ethics frameworks have made important contributions to governance discourse, particularly in their treatment of fairness, accountability, transparency, and safety. Yet, even in their most sophisticated forms, these frameworks remain structurally incomplete: they insufficiently theorize the affective and culturally mediated realities through which human beings encounter technological systems. This article argues that current AI ethics remains overly procedural and therefore cannot fully account for the human terms on which artificial intelligence is experienced and judged. A central asymmetry underlies the field: significant effort is devoted to developing systems capable of detecting, simulating, and responding to human emotion, while the dominant ethical frameworks used to evaluate those same systems routinely treat emotion as analytically secondary or marginalized. This asymmetry operates across three analytically distinct levels. At the technical level, systems detect or simulate emotional states while their designers lack an ethical vocabulary for what is at stake in those operations. At the governance level, frameworks that evaluate those systems provide no category for affective harm. At the level of lived experience, the people subjected to AI systems encounter them through feeling, embodiment, and cultural interpretation, dimensions that procedural evaluation does not reach. Emotion recognition offers a clear illustration of the consequences: insufficient consideration of emotion at the technical level produces systems that misread culturally specific expression; insufficient consideration at the governance level means no ethical framework names the misrecognition as a harm; insufficient consideration at the level of experience means the affected person has no recourse within existing evaluative categories. This asymmetry reflects a foundational limitation in prevailing models of responsible AI, which are sophisticated in evaluating systems while remaining underdeveloped in theorizing how those systems are lived by the people whose lives they shape (Floridi et al. 2018; Jobin et al. 2019; Choung et al. 2023). Drawing on affect theory, cultural studies, and sociotechnical scholarship, this article argues for a paradigm shift in how AI ethics conceptualizes human experience, one that moves beyond procedural compliance toward a richer account of lived ethical life.
Sharon Tettegah (Sun,) studied this question.