Generative artificial intelligence and affective injustice in education

Generative artificial intelligence (GenAI) has transformed educational debates by raising important questions about learning, assessment, academic integrity, and epistemic injustice. This paper argues that these discussions overlook another equally significant issue: how GenAI participates in students’ affective formation. Drawing on recent philosophical work on affective injustice, I reconceptualize this concept for educational contexts by arguing that affective injustice concerns unjust interference with the processes through which students develop as affective subjects. I theorize GenAI as an affective technology that shapes emotional norms, orientations, and capacities through interactions involving encouragement, reassurance, emotional feedback, and simulated empathy. I then identify two mechanisms through which GenAI may contribute to affective injustice—affective normalization and affective dependency—and examine their implications for educational philosophy and practice. Finally, I propose principles for affectively just educational AI that preserve affective plurality, cultivate affective agency, and support the relational and reflective purposes of education.