VET: A Framework for Analyzing AI Discourse

• URL: http://arxiv.org/abs/2606.01929v2
• Date: Tue, 09 Jun 2026 14:23:44 GMT
• Title: VET: A Framework for Analyzing AI Discourse
• Abstract summary: Public discourse on AI has become polarized; exaggerated positions on AI in traditional and social media threaten the development of AI Literacy.<n>I introduce the VET Framework, a method for categorizing AI discourse along the dimensions of valence, effectiveness, and trajectory.<n>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.
• Score: 9.692439869431833
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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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