Reading the Room? Apparently Not: When LLMs Miss Intent
Opening — Why this matters now Large Language Models are increasingly deployed in places where misunderstanding intent is not a harmless inconvenience, but a real risk. Mental‑health support, crisis hotlines, education, customer service, even compliance tooling—these systems are now expected to “understand” users well enough to respond safely. The uncomfortable reality: they don’t. The paper behind this article demonstrates something the AI safety community has been reluctant to confront head‑on: modern LLMs are remarkably good at sounding empathetic while being structurally incapable of grasping what users are actually trying to do. Worse, recent “reasoning‑enabled” models often amplify this failure instead of correcting it. fileciteturn0file0 ...