AI discourse employs strategically polysemous terms that blend technical precision with anthropomorphic implications, enabling glosslighting that sustains hype and deflects scrutiny.
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3 Pith papers cite this work, alongside 9 external citations. Polarity classification is still indexing.
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Hiding generative AI use to signal expertise reduces knowledge sharing and transparency among workplace colleagues.
Human tests should not be applied to AI to measure traits like intelligence due to calibration, validity, contamination, and prompt sensitivity issues; develop AI-specific evaluation frameworks instead.
citing papers explorer
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Strategic Polysemy in AI Discourse: A Philosophical Analysis of Language, Hype, and Power
AI discourse employs strategically polysemous terms that blend technical precision with anthropomorphic implications, enabling glosslighting that sustains hype and deflects scrutiny.
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"If You're Very Clever, No One Knows You've Used It": The Social Dynamics of Developing Generative AI Literacy in the Workplace
Hiding generative AI use to signal expertise reduces knowledge sharing and transparency among workplace colleagues.
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Position: Stop Evaluating AI with Human Tests, Develop Principled, AI-specific Tests instead
Human tests should not be applied to AI to measure traits like intelligence due to calibration, validity, contamination, and prompt sensitivity issues; develop AI-specific evaluation frameworks instead.