A Multidisciplinary Lens of Bias in Hate Speech

Reyero Lobo, Paula; Kwarteng, Joseph; Russo, Mayra; Fahimi, Miriam; Scott, Kristen; Ferrara, Antonio; Sen, Indira and Fernandez, Miriam (2023). A Multidisciplinary Lens of Bias in Hate Speech. In: The 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 6-9 Nov 2023, Kusadasi, Turkey.

DOI: https://doi.org/10.1145/3625007.3627491


Hate speech detection systems may exhibit discriminatory behaviours. Research in this field has focused primarily on issues of discrimination toward the language use of minoritised communities and non-White aligned English. The interrelated issues of bias, model robustness, and disproportionate harms are weakly addressed by recent evaluation approaches, which capture them only implicitly. In this paper, we recruit a multidisciplinary group of experts to bring closer this divide between fairness and trustworthy model evaluation. Specifically, we encourage the experts to discuss not only the technical, but the social, ethical, and legal aspects of this timely issue. The discussion sheds light on critical bias \emph{facets} that require careful considerations when deploying hate speech detection systems in society. Crucially, they bring clarity to different approaches for assessing, becoming aware of bias from a broader perspective, and offer valuable recommendations for future research in this field.

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