# The Role of Generative AI in Facilitating Social Interactions: A Scoping Review

arXiv: https://arxiv.org/abs/2506.10927 · HTML: https://mlsanity.com/paper/2506.10927/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 109 references that are in the map.
- First posted on arXiv 12 Jun 2025.

## Builds on (most cited first, 17 of 17)

- [Ethical and social risks of harm from Language Models](https://mlsanity.com/paper/2112.04359/) (2021)
- [Generative AI](https://mlsanity.com/paper/2309.07930/) (2023)
- [Participation is not a Design Fix for Machine Learning](https://mlsanity.com/paper/2007.02423/) (2020)
- [The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice](https://mlsanity.com/paper/2310.00907/) (2023)
- [Fairness And Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, And Mitigation Strategies](https://mlsanity.com/paper/2304.07683/) (2023)
- [Generative Artificial Intelligence: A Systematic Review and Applications](https://mlsanity.com/paper/2405.11029/) (2024)
- [Queer In AI: A Case Study in Community-Led Participatory AI](https://mlsanity.com/paper/2303.16972/) (2023)
- [ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events](https://mlsanity.com/paper/2309.12244/) (2023)
- [Mapping the Ethics of Generative AI: A Comprehensive Scoping Review](https://mlsanity.com/paper/2402.08323/) (2024)
- [PeerGPT: Probing the Roles of LLM-based Peer Agents as Team Moderators and Participants in Children's Collaborative Learning](https://mlsanity.com/paper/2403.14227/) (2024)
- [Towards Designing a ChatGPT Conversational Companion for Elderly People](https://mlsanity.com/paper/2304.09866/) (2023)
- ["It's the only thing I can trust": Envisioning Large Language Model Use by Autistic Workers for Communication Assistance](https://mlsanity.com/paper/2403.03297/) (2024)
- [Ain't Misbehavin' -- Using LLMs to Generate Expressive Robot Behavior in Conversations with the Tabletop Robot Haru](https://mlsanity.com/paper/2402.11571/) (2024)
- [Exploring the Design of Generative AI in Supporting Music-based Reminiscence for Older Adults](https://mlsanity.com/paper/2403.01413/) (2024)
- ["When He Feels Cold, He Goes to the Seahorse"-Blending Generative AI into Multimaterial Storymaking for Family Expressive Arts Therapy](https://mlsanity.com/paper/2402.06472/) (2024)
- ["My lollipop dropped..."-Probing Design Opportunities for SEL Agents through Children's Peer Co-Creation of Social-Emotional Stories](https://mlsanity.com/paper/2403.03618/) (2024)
- [Unlocking Memories with AI: Exploring the Role of AI-Generated Cues in Personal Reminiscing](https://mlsanity.com/paper/2404.11227/) (2024)

## Built on by (most cited first, 1 of 1)

- ["Not Human, Funnier": How Machine Identity Shapes Humor Perception in Online AI Stand-up Comedy](https://mlsanity.com/paper/2602.12763/) (2026)

## Abstract (arXiv)

Reduced social connectedness increasingly poses a threat to mental health, life expectancy, and general well-being. Generative AI (GAI) 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 GAI-based applications are currently designed to facilitate social interaction, what forms of social engagement they target, and which design and evaluation methodologies designers use to create and evaluate them. Through an analysis of 30 studies published since 2020, 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 GAI to support dynamic and personalized interactions, but calls for greater attention to equitable design practices and inclusive evaluation strategies.