AI RESEARCH
From Sycophancy to Sensemaking: Premise Governance for Human-AI Decision Making
arXiv CS.CL
•
ArXi:2602.02378v2 Announce Type: replace As LLMs expand from assistance to decision, a dangerous pattern emerges: fluent agreement without calibrated judgment. Low-friction assistants can become sycophantic, baking in implicit assumptions and pushing verification costs onto experts, while outcomes arrive too late to serve as reward signals. In deep-uncertainty decisions (where objectives are contested and reversals are costly), scaling fluent agreement amplifies poor commitments faster than it builds expertise.