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VET: A Framework for Analyzing AI Discourse

arXiv 2606.01929 ↗First posted 1 Jun 2026cs.AIcited by 0

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Abstract (arXiv)

Public discourse on AI has become polarized; exaggerated positions on AI in traditional and social media threaten the development of AI Literacy among the general public. In this article, I introduce the VET Framework, a method for categorizing AI discourse along the dimensions of valence, effectiveness, and trajectory. I show how this framework can be used to identify, compare, and critique prevalent narratives of AI Hype, AI Doom, AI Denial, and AI Normalcy. Using VET, I analyze how each of these four stances exaggerates some aspects of the current state and/or likely evolution of AI, and illustrate how the VET framework can serve as an AI Literacy tool by supporting the ``vetting'' of polarized AI discourse.

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References · 14

  1. 2020Scaling Laws for Neural Language Modelscited by 6,586
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2 more
  1. 2024Misrepresented Technological Solutions in Imagined Futures: The Origins and Dangers of AI Hype in the Research Communitycited by 3
  2. 2026AI and Consciousness: Shifting Focus Towards Tractable Questionscited by 1

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