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

2026-04-22

AI Summary

This study addresses how metaphorical terms such as “hallucination,” “alignment,” and “agent” in artificial intelligence are deployed with strategic polysemy—maintaining narrow technical definitions while evoking anthropomorphic associations. Such usage obscures technical substance, fuels hype, and misleads public and policy understanding. The paper introduces the novel theoretical framework of “strategic polysemy” and “glosslighting,” integrating philosophical analysis, discourse analysis, and conceptual modeling through interdisciplinary lenses from linguistics and Science and Technology Studies (STS). It demonstrates how semantic strategies in AI discourse sustain cycles of hype, shape resource allocation, and circumvent ethical scrutiny. By exposing these rhetorical mechanisms, the work offers a critical linguistic pathway for more transparent and accountable AI governance.

Technology Category

• Philosophy and Ethics of AI: AI & Epistemology
• Natural Language Processing: Discourse, Pragmatics & Argument Mining
• Humans and AI: Understanding People, Theories, Concepts and Methods

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search
• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions

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.

Problem

• strategic polysemy
• glosslighting
• AI discourse
• anthropomorphism
• language and power

Innovation

• strategic polysemy
• glosslighting
• AI discourse
• anthropomorphism
• sociotechnical language