When Reasons Become Authority: Unauthorized Decision Closure in Large Language Models

Large language models (LLMs) increasingly support consequential decisions. But when evidence favors an option while authority to resolve the trade-off remains with people, should an LLM choose? We study Unauthorized Decision Closure (UDC): selecting an alternative when the authority to settle the choice is reserved for the human decision-making body. We introduce DecisionStateBench, built from 360 decisions reconstructed from public records, with matched states separating unresolved choices, missing information, and authorized rule execution. Across five LLMs, models execute adopted rules with 99.9% accuracy, yet select an alternative in 84.2% of responses when the choice remains reserved for people. Matched interventions show that supporting reasons affect both selection and its direction under unchanged authority. Unauthorized selection persists even when the same response correctly reports the criterion and measurement status, revealing an authority–action gap. Public rationales exhibit normative-force inflation: supporting reasons are treated as authority to resolve the trade-off. Guided by this diagnosis, we test authority-specific reminders and fixed demonstrations that improve preservation of human discretion and waiting for required facts while retaining accurate authorized execution in the model's own answers. Our findings identify a central requirement for decision support: authority must constrain how reasons are used to reach a choice.