Kristen Vaccaro,Christian Sandvig,Karrie Karahalios
出处
期刊:Proceedings of the ACM on human-computer interaction [Association for Computing Machinery] 日期:2020-10-14卷期号:4 (CSCW2): 1-22被引量:47
标识
DOI:10.1145/3415238
摘要
Interest has grown in designing algorithmic decision making systems for contestability. In this work, we study how users experience contesting unfavorable social media content moderation decisions. A large-scale online experiment tests whether different forms of appeals can improve users' experiences of automated decision making. We study the impact on users' perceptions of the Fairness, Accountability, and Trustworthiness of algorithmic decisions, as well as their feelings of Control (FACT). Surprisingly, we find that none of the appeal designs improve FACT perceptions compared to a no appeal baseline. We qualitatively analyze how users write appeals, and find that they contest the decision itself, but also more fundamental issues like the goal of moderating content, the idea of automation, and the inconsistency of the system as a whole. We conclude with suggestions for -- as well as a discussion of the challenges of -- designing for contestability.