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Artificial intelligence (AI) has become prevalent in our everydaytechnologies and impacts both individuals and communities. The explainable AI(XAI) scholarship has explored the philosophical nature of explanation andtechnical explanations, which are usually driven by experts in lab settings andcan be challenging for laypersons to understand. In addition, existing XAIresearch tends to focus on the individual level. Little is known about howpeople understand and explain AI-led decisions in the community context.Drawing from XAI and activity theory, a foundational HCI theory, we theorizehow explanation is situated in a community's shared values, norms, knowledge,and practices, and how situated explanation mediates community-AI interaction.We then present a case study of AI-led moderation, where community memberscollectively develop explanations of AI-led decisions, most of which areautomated punishments. Lastly, we discuss the implications of this framework atthe intersection of CSCW, HCI, and XAI.

Mediating Community-AI Interaction through Situated Explanation: The Case of AI-Led Moderation