Artificial Intolerance: Stigmatizing Language in Clinical Documentation Skews Large Language Model Decision-Making

ArXi:2605.17228v1 Announce Type: new Large Language Models (LLMs) are increasingly deployed in high-stakes domains such as clinical decision and medical documentation. However, the robustness of these models against subtle linguistic variations, specifically stigmatizing language (SL) commonly found in human-authored clinical notes, remains critically under-explored. In this work, we investigate whether frontier LLMs inherit and propagate this human bias when processing clinical text.