探索生成式AI如何设计社交应用，助力人际连接。
The Role of Generative AI in Facilitating Social Interactions: A Scoping Review
- 分析30项研究，梳理GAI在故事创作等场景中的社交应用设计
- 发现参与式设计能提升技术使用效果与社会互动质量
- 提醒关注文化偏见和可及性问题，倡导公平设计
社会联结减弱正威胁心理健康、寿命与整体福祉。生成式AI（GAI）技术如大语言模型（LLMs）和图像生成工具，正被广泛应用于增强人类社交体验。尽管其影响力日益增长，但对这些技术如何影响社交互动仍知之甚少。本范围综述分析了2020年以来30项研究，探讨基于GAI的应用如何设计以促进社交互动，其目标的社交形式，以及设计与评估方法。研究覆盖故事讲述、社交情感技能训练、回忆疗法、协作学习、音乐创作及日常对话等应用领域。强调参与式与共同设计方法在促进有效技术使用与社会参与中的作用，同时审视文化偏见与可及性等社会伦理问题。本综述指出GAI支持动态个性化互动的巨大潜力，但呼吁更多关注公平设计实践与包容性评估策略。
原文摘要 · Abstract (English)
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.
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