The role of generative AI in facilitating social interactions: A scoping review

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Authors: Teis Arets, Giulia Perugia, Maarten Houben, Wijnand A. IJsselsteijn
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Abstract

Social interaction is fundamental to human well-being. A lack of social interaction contributes to feelings of social isolation and loneliness. Generative AI (GenAI) technologies, such as large language models (LLMs) and image generation tools, are increasingly integrated into applications aimed at enhancing human social experiences. Despite their growing presence, little is known about how these technologies influence social interactions. This scoping review investigates how GenAI-based applications are designed to facilitate social interaction, what forms of social engagement they target, and which design and evaluation methodologies are used to develop and evaluate them. Through an analysis of 30 studies published up to July 2024, we identify key trends in application domains including storytelling, socio-emotional skills training, reminiscence, collaborative learning, music making, and general conversation. We highlight the role of participatory and co-design approaches in fostering both effective technology use and social engagement, while also examining socio-ethical concerns such as cultural bias and accessibility. This review underscores the potential of GenAI to support dynamic and personalized interactions, but calls for greater attention to equitable design practices and inclusive evaluation strategies.

Fields of Study & Subjects

Innovative Human-Technology Interaction Digital Mental Health Interventions Mental Health via Writing

Publication details

Journal / source
Computers in Human Behavior Reports
Volume
24
Pages
101300–101300
Publication date
15 September 2026
Language
EN