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

Published: 15 October 2020 Publication History

Abstract

Artificial intelligence (AI) has become prevalent in our everyday technologies and impacts both individuals and communities. The explainable AI (XAI) scholarship has explored the philosophical nature of explanation and technical explanations, which are usually driven by experts in lab settings and can be challenging for laypersons to understand. In addition, existing XAI research tends to focus on the individual level. Little is known about how people understand and explain AI-led decisions in the community context. Drawing from XAI and activity theory, a foundational HCI theory, we theorize how 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 members collectively develop explanations of AI-led decisions, most of which are automated punishments. Lastly, we discuss the implications of this framework at the intersection of CSCW, HCI, and XAI.

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    cover image Proceedings of the ACM on Human-Computer Interaction
    Proceedings of the ACM on Human-Computer Interaction  Volume 4, Issue CSCW2
    CSCW
    October 2020
    2310 pages
    EISSN:2573-0142
    DOI:10.1145/3430143
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    Published: 15 October 2020
    Published in PACMHCI Volume 4, Issue CSCW2

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    Author Tags

    1. accountability
    2. ai
    3. artificial intelligence
    4. automated moderation
    5. community-ai interaction
    6. explainable ai
    7. explanation
    8. human-ai interaction
    9. online community.
    10. transparency

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