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arXiv:2604.21043cs.CY

Strategic Polysemy in AI Discourse: A Philosophical Analysis of Language, Hype, and Power

Travis LaCroix, Fintan Mallory, Sasha Luccioni

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Abstract

This paper examines the strategic use of language in contemporary artificial intelligence (AI) discourse, focusing on the widespread adoption of metaphorical or colloquial terms like "hallucination", "chain-of-thought", "introspection", "language model", "alignment", and "agent". We argue that many such terms exhibit strategic polysemy: they sustain multiple interpretations simultaneously, combining narrow technical definitions with broader anthropomorphic or common-sense associations. In contemporary AI research and deployment contexts, this semantic flexibility produces significant institutional and discursive effects, shaping how AI systems are understood by researchers, policymakers, funders, and the public. To analyse this phenomenon, we introduce the concept of glosslighting: the practice of using technically redefined terms to evoke intuitive -- often anthropomorphic or misleading -- associations while preserving plausible deniability through restricted technical definitions. Glosslighting enables actors to benefit from the persuasive force of familiar language while maintaining the ability to retreat to narrower definitions when challenged. We argue that this practice contributes to AI hype cycles, facilitates the mobilisation of investment and institutional support, and influences public and policy perceptions of AI systems, while often deflecting epistemic and ethical scrutiny. By examining the linguistic dynamics of glosslighting and strategic polysemy, the paper highlights how language itself functions as a sociotechnical mechanism shaping the development and governance of AI.

arXiv comments
Accepted in the Ninth Annual ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) 2026
Journal reference
DOI
doi:10.1145/3805689.3812399
Subjects
cs.CYComputers and Society cs.AIArtificial Intelligence cs.LGMachine Learning

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