AI-Generated Feedback and Its Effects on User Emotional Experience

Abstract

As artificial intelligence (AI) systems increasingly participate in human communication—from educational platforms and workplace tools to customer service interactions—AI-generated feedback has become a meaningful component of everyday digital experience. While research has traditionally examined the accuracy and usefulness of AI-generated responses, far less attention has been directed toward how such feedback shapes users’ emotional states. This article investigates the emotional consequences of AI-generated feedback, integrating insights from human–computer interaction (HCI), psychology, affective computing, and communication studies. Drawing from theoretical frameworks such as social presence theory, appraisal theory, and computer-mediated communication models, it analyzes how tone, content, personalization, and conversational dynamics within AI-generated feedback influence user emotional experience. A methodological overview highlights approaches used in recent research, including qualitative analysis, sentiment coding, controlled experiments, and computational modeling. Findings reveal that AI-generated feedback can evoke a spectrum of emotional reactions—ranging from reassurance and motivation to frustration, anxiety, or emotional detachment—depending on its linguistic features, contextual fit, and perceived empathy. The article concludes with implications for ethical design, emotional safety, and future research directions.