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

TL;DR

This paper analyzes how strategic polysemy and glosslighting in AI discourse influence perceptions, hype, and policy by blending technical and anthropomorphic language to shape understanding and support.

Contribution

It introduces the concept of glosslighting to explain how flexible language use sustains AI hype and institutional support while maintaining plausible deniability.

Findings

Glosslighting combines technical and intuitive meanings to influence perceptions.

Strategic polysemy sustains multiple interpretations of AI terms.

Language practices shape AI development, hype, and governance.

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.