Care, Wisdom, and Civics: Value Sensitive Design of Large Language Model Support for Online Moderation

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Authors: Lovely-Frances Domingo, Sarah Gilbert, Yang Trista Cao, Hal Daumé, Michelle L. Mazurek, Katie Shilton
Cited by: 0
References: 23

Abstract

Human–computer interaction (HCI) and natural language processing (NLP) research increasingly explore large language model (LLM) support for online content moderation tasks. This study conducts a value sensitive design process with volunteer moderators of two heavily moderated subreddits (history Q&A, and legal advice). Through an empirical investigation using iterative interviews and a conceptual investigation centered in virtue ethics, we find moderators center values of care, wisdom, and civics in their work. A technical investigation then matches these values to the known capabilities and limitations of LLMs. We find current LLMs potentially well-suited to supporting care in managing sensitive content and wisdom in bridging content to context. However, many aspects of civic community-building are challenging to support with today’s models. Our study provides guidelines for designing LLM support for moderation tools and demonstrates value sensitive design methods to connect work practices, values, and the possibilities and limits of automation.

Fields of Study & Subjects

Ethics and Social Impacts of AI Hate Speech and Cyberbullying Detection Artificial Intelligence in Law

Publication details

Journal / source
ACM Transactions on Computer-Human Interaction
Volume
33
Issue
3
Pages
1–27
Publication date
7 February 2026
Language
EN