Designing Emotion-Adaptive Human–AI Interfaces: An Empirical Study on Empathy, Trust, and Context-Aware Interaction
Keywords:
Emotion-Adaptive Interaction, Human–AI Interfaces, Empathy in Human–Computer Interaction, Context-Aware SystemsAbstract
As artificial intelligence systems become increasingly embedded in
everyday human–computer interaction contexts, user expectations regarding their
social and emotional capabilities are gradually shifting from a primary focus on
functional efficiency toward more complex dimensions such as empathetic
experience, trust formation, and contextual sensitivity. Nevertheless, despite the
notable progress achieved by large language models in terms of linguistic fluency,
such systems often remain confined to surface-level simulations of empathy. In
response to this limitation, the present study investigates an emotion-adaptive
human–AI interface that integrates real-time affect recognition, dynamic user
profiling, and context-aware response modulation within a unified framework.
Through a comparative user study encompassing task-oriented, social, and
emotionally supportive scenarios, the results suggest that emotion-adaptive
mechanisms may, to some extent, enhance users’ perceived empathy, trust, and
engagement.
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