Can Generative AI help people navigate Radical Moral Disagreements? The CONSIDER prototype
2026-05-29 • Human-Computer Interaction
Human-Computer Interaction
AI summaryⓘ
The authors discuss how big disagreements about morals, called Radical Moral Disagreements (RMDs), are causing stress and are often shut down in conversations. They suggest that large language models (LLMs), like AI chatbots, could help people talk through these tough disagreements more thoughtfully. To do this, they created a tool called CONSIDER that helps a person explore different viewpoints by showing an opposing opinion made by an AI, encouraging reflection and clearer thinking. The paper also explains how CONSIDER was designed and looks at possible risks of using AI in this way.
Radical Moral DisagreementsPolarisationLarge Language ModelsDemocratic DeliberationMoral ReasoningMill's Epistemic Value of DisagreementCONSIDERValue ClarificationAI EthicsOpinion Navigation
Authors
William Hohnen-Ford, Sarah Chen, Kathryn B. Francis, Madeline G. Reinecke, Ilina Singh, David Lyreskog
Abstract
Radical Moral Disagreements (RMDs) are highly polarising topics that are increasingly censored in everyday life, with growing evidence suggesting that this polarisation carries measurable costs to public mental health. To address these challenges, some researchers have proposed Large Language Models (LLMs) as a means to support more democratic deliberation and better moral reasoning. Yet existing tools are poorly calibrated to help people navigate RMDs, because of their intense and divisive characteristics. This paper introduces CONSIDER, a prototype for a one-to-one AI tool for RMD navigation. Drawing on Mill's account of the epistemic value of disagreement, CONSIDER aims at value clarification through structured disagreement with an opposing LLM-generated opinion. We describe CONSIDER's design logic and analyse potential risks posed by such tools to guide future development.