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

arXiv: https://arxiv.org/abs/2604.21043 · HTML: https://mlsanity.com/paper/2604.21043/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning.
- Builds on 28 of its 119 references that are in the map.
- First posted on arXiv 22 Apr 2026.

## Placed in

- LLM reasoning / [Reasoning benchmarks and evaluation](https://mlsanity.com/lr/reasoning-benchmarks-and-evaluation/)

## Builds on (most cited first, 28 of 28)

- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [Qwen3 Technical Report](https://mlsanity.com/paper/2505.09388/) (2025)
- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [Artificial Intelligence, Values and Alignment](https://mlsanity.com/paper/2001.09768/) (2020)
- [Agentic Misalignment: How LLMs Could Be Insider Threats](https://mlsanity.com/paper/2510.05179/) (2025)
- [Looking Inward: Language Models Can Learn About Themselves by Introspection](https://mlsanity.com/paper/2410.13787/) (2024)
- [Emergent Introspective Awareness in Large Language Models](https://mlsanity.com/paper/2601.01828/) (2026)
- [Language Models Are Capable of Metacognitive Monitoring and Control of Their Internal Activations](https://mlsanity.com/paper/2505.13763/) (2025)
- [The Grey Hoodie Project: Big Tobacco, Big Tech, and the threat on academic integrity](https://mlsanity.com/paper/2009.13676/) (2020)
- [AI Hallucinations: A Misnomer Worth Clarifying](https://mlsanity.com/paper/2401.06796/) (2024)
- [Mirages: On Anthropomorphism in Dialogue Systems](https://mlsanity.com/paper/2305.09800/) (2023)
- [Language Models as Models of Language](https://mlsanity.com/paper/2408.07144/) (2024)
- [Position: Key Claims in LLM Research Have a Long Tail of Footnotes](https://mlsanity.com/paper/2308.07120/) (2023)
- [Do Language Models' Words Refer?](https://mlsanity.com/paper/2308.05576/) (2023)
- [The Contestation of Tech Ethics: A Sociotechnical Approach to Technology Ethics in Practice](https://mlsanity.com/paper/2106.01784/) (2021)
- [Metaethical Perspectives on 'Benchmarking' AI Ethics](https://mlsanity.com/paper/2204.05151/) (2022)
- [Studying Up Machine Learning Data: Why Talk About Bias When We Mean Power?](https://mlsanity.com/paper/2109.08131/) (2021)
- [Dehumanizing Machines: Mitigating Anthropomorphic Behaviors in Text Generation Systems](https://mlsanity.com/paper/2502.14019/) (2025)
- [Watching the Generative AI Hype Bubble Deflate](https://mlsanity.com/paper/2408.08778/) (2024)
- [Est-ce que vous compute? Code-switching, cultural identity, and AI](https://mlsanity.com/paper/2112.08256/) (2021)
- [Moral Dilemmas for Moral Machines](https://mlsanity.com/paper/2203.06152/) (2022)
- [The Language Labyrinth: Constructive Critique on the Terminology Used in the AI Discourse](https://mlsanity.com/paper/2307.10292/) (2023)
- [On the referential capacity of language models: An internalist rejoinder to Mandelkern & Linzen](https://mlsanity.com/paper/2406.00159/) (2024)
- [How ChatGPT Changed the Media's Narratives on AI: A Semi-Automated Narrative Analysis Through Frame Semantics](https://mlsanity.com/paper/2408.06120/) (2024)
- [Research as Resistance: Recognizing and Reconsidering HCI's Role in Technology Hype Cycles](https://mlsanity.com/paper/2504.08336/) (2025)
- [Deep Hype in Artificial General Intelligence: Uncertainty, Sociotechnical Fictions and the Governance of AI Futures](https://mlsanity.com/paper/2508.19749/) (2025)
- [Empirical AI Ethics: Reconfiguring Ethics towards a Situated, Plural, and Transformative Approach](https://mlsanity.com/paper/2509.17727/) (2025)
- [AI Narrative Breakdown. A Critical Assessment of Power and Promise](https://mlsanity.com/paper/2601.22255/) (2026)

## Built on by (most cited first, 1 of 1)

- [The Epistemic Politics of AI Anthropomorphism](https://mlsanity.com/paper/2608.00961/) (2026)

## Abstract (arXiv)

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.