Artificial Intelligence-Augmented Social Interfaces: Towards Empathetic and Context-Aware Interaction Systems

Abstract

The rapid evolution of artificial intelligence (AI) has led to the emergence of socially intelligent systems capable of dynamic, human-centered interaction. However, realizing truly meaningful and empathetic communication remains a key challenge, especially when AI must interpret not only what users say, but also what they mean and feel within a rich social context. This paper proposes a framework for AI-augmented social interfaces (AISI) that combine transformer-based dialogue generation, real-time sentiment analysis, and user profile modeling. The system adapts its tone, engagement level, and responses based on emotional cues, behavioral patterns, and environmental context. A three-phase user study with 60 participants showed that the AISI outperformed a traditional rule-based chatbot across task completion, user trust, and emotional resonance. We also address ethical concerns around transparency, privacy, and explainability, suggesting pathways toward socially responsible AI design. Our findings are relevant to domains such as digital health, education, and collaborative systems where trust and emotional intelligence are essential.

Keywords: Artificial Intelligence, Social Computing, Empathetic Interaction, Affective Computing

DOI: 10.54941/ahfe1006938