Understanding the Design Space of AI-Mediated Social Interaction in Online Learning: Challenges and Opportunities

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Nowadays, our online interactions are constantly mediated through Artificial Intelligence (AI), including our social interactions. AI-mediated social interaction is the AI-facilitated process of building and maintaining social connections between individuals through information inferred from people's online posts. With its impending application across a wide range of contexts, the challenges and opportunities of AI-mediated social interaction remain underexplored. This paper seeks to understand the design space of AI-mediated social interaction in the context of online learning, where online learners frequently experience social isolation. We deployed an AI agent named SAMI in three online class discussion forums to help online learners build social connections. Using SAMI as a probe, we conducted semi-structured interviews with 26 online learners to elicit design feedback by understanding their difficulties in remote social interactions and their experiences with SAMI. Through the lenses of social translucence and social-technical gap, we illustrate online learners' difficulties in remote social interactions and how SAMI resolved some of the difficulties. We also identify potential ethical and social challenges of SAMI such as user agency and privacy. Based on our findings, we outline the design space of AI-mediated social interaction. We discuss the design tension between AI performance and ethical design and pinpoint two design opportunities for AI-mediated social interaction in designing towards human-AI collaborative social matching and artificial serendipity.