Abstract
This review paper provides a conceptualization of AI-assisted content moderation with various degrees of autonomy and summarizes experimental evidence for how different levels of automation in content moderation and related losses of autonomy affect individuals and groups. Our results show that current research predominantly focuses on individuallevel effects, necessitating a shift toward understanding the impact on groups. The study highlights gaps in exploring different levels of AI-assisted moderation interventions and misalignments of different conceptualizations that make comparing research results difficult. The discussion underscores the prevailing emphasis on harmful content removal and advocates for investigating more constructive moderation techniques, emphasizing the potential of AI in fostering normative, higher-level outcomes.
DOI
10.30658/hmc.9.10
Author ORCID Identifier
Zehui Yu: 0009-0003-1728-7829
Luckas Otto: 0000-0002-4374-6924
Dennis Assenmacher: 0000-0001-9219-1956
Claudia Wagner: 0000-0002-0640-8221
Recommended Citation
Yu, Z., Otto, L., Assenmacher, D., & Wagner, C. (2024). A systematic review of the effects of AI-assisted moderation on individuals and groups. Human-Machine Communication, 9, 167–188. https://doi.org/10.30658/hmc.9.10
Included in
Artificial Intelligence and Robotics Commons, Communication Technology and New Media Commons, Other Communication Commons, Social Media Commons
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