Ethical Concerns in Neurolinguistic Emotion Inference by AI

Abstract

Artificial intelligence (AI) systems that infer human emotional and cognitive states using linguistic and neurolinguistic cues drawn from speech and text are becoming increasingly common. These include lexical choice, syntax, prosody, discourse structure, hesitation patterns, and other language-based features associated with cognitive load, affect, or intention. While such systems promise advancements in education, mental-health support, accessibility, and human-computer interaction, they raise significant ethical concerns. These involve privacy, bias, the validity of linguistic-to-emotional mapping, cultural variation in expression, overreach in surveillance contexts, and unclear accountability. This article synthesizes current research on the linguistic foundations of emotion and cognition inference, analyzes associated ethical risks, and outlines recommendations for responsible development and deployment.