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May 25, 2026
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Aug 17, 2026
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Abstract

The unregulated proliferation of hate speech, defined as any expression of beliefs that incite hatred, discrimination, or violence against individuals or social groups (Fortuna & Nunes, 2018), in social media has called into question the efficacy of removal-based content moderation and has driven the need to explore alternative approaches. AI-generated counterspeech could be a scalable and cost-effective intervention (Ashida & Komachi, 2022). Counterspeech is defined as a direct response to hate speech aimed at refuting or undermining it (Wachs et al., 2023). Research in this growing field is fragmented across computational linguistics and social sciences, lacking systematic methods to define and evaluate effective counterspeech, revealing a gap between AI's technical capabilities and evidenced social impact.
This review aims to examine evidence from these two fields to identify the differing conceptualizations of counterspeech, map the collaborative approaches used for counterspeech generation and evaluation, and examine the alignment between stated research goals (e.g., reducing hate speech in digital environments) and the operational measures employed to identify them.
Only a few studies evaluate counterspeech in real-world interactive settings or measure long-term impact. We identify some key misalignments, such as the reliance on text metrics and human or artificial annotators as proxies for complex social interventions, instead of integrating psychological and behavioral measures. We propose a linked approach to counterspeech that links theoretical frameworks, procedures, measurements and research goals from the perspective of both psychology and computational linguistics to identify promising directions for future interdisciplinary collaboration and more socially meaningful AI-assisted interventions.

Keywords

Counter-Speech Artificial Intelligence Large Language Models Human Augmentation

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How to Cite
Cosola, A., Paciello, M., Pollini, A., & D’Errico, F. (2026). Beyond automation: the collaborative role of AI in countering Hate Speech. A scoping review. Journal of E-Learning and Knowledge Society, 22(1), 75-90. https://doi.org/10.20368/1971-8829/1136378

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