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Contestability For Content Moderation

Kristen Vaccaro, Ziang Xiao, Kevin Hamilton, Karrie Karahalios

2021Proceedings of the ACM on Human-Computer Interaction73 citationsDOIOpen Access PDF

Abstract

Content moderation systems for social media have had numerous issues of bias, in terms of race, gender, and ability among many others. One proposal for addressing such issues in automated decision making is by designing for contestability, whereby users can shape and influence how decisions are made. In this study, we conduct a series of participatory design workshops with participants from communities that have experienced problems with social media content moderation in the past. Together with participants, we explore the idea of designing for contestability in content moderation and find that users' designs suggest three fruitful, practical avenues: adding representation, improving communication, and designing with compassion. We conclude with design recommendations drawn from participants' proposals, and reflect on the challenges that remain.

Topics & Concepts

ModerationCompassionCitizen journalismPsychologySocial mediaSocial psychologyContent (measure theory)Computer scienceWorld Wide WebPolitical scienceMathematicsLawMathematical analysisHate Speech and Cyberbullying DetectionEthics and Social Impacts of AIInnovative Human-Technology Interaction
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