Artificial Intelligence (AI) can produce answers that sound convincing and reasonable. But sounding reasonable is not the same as reasoning well. We compared 60 AI models with citizens who deliberated on complex public issues by exchanging reasons, considering different viewpoints, and reflecting on their positions. We asked whether AI connects reasons to decisions in the same structured way people do after deliberation. Most models did not. Their answers often sounded persuasive, but the reasons they gave were not consistently connected to their conclusions. This gap between sounding reasonable and reasoning coherently matters as AI is increasingly used to support decisions on complex public issues. Our findings show that a plausible answer is not necessarily a well-reasoned one. AI may therefore be more useful for helping people explore and compare different arguments than for making complex judgments on their behalf

Large Language Models (LLMs) are entering democratic contexts as instruments of governance, where the challenges at hand are ill-structured, marked...

Large Language Models (LLMs) are entering democratic contexts as instruments of governance, where the challenges at hand are ill-structured, marked...

Institutional configurations and deliberative innovation: A comparative analysis of minipublic adoption across advanced democracies

This article proposes a methodological framework that combines a Q-concourse questionnaire with Multiple Factor Analysis and Hierarchical Clustering on Principa...

Deliberative reason and the effect of minipublic configurations

Radical right-wing groups are often linked to conspiratorial beliefs that can fuel political extremism but understanding how these beliefs translate into real-world action remains a challenge, as the....

Radical right-wing groups are often linked to conspiratorial beliefs that can fuel political extremism but understanding how these beliefs translate into real-world action remains a challenge, as the...