VET: A Framework for Analyzing AI Discourse

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.

Artificial Intelligence (cs.AI)

arXiv:2606.01929 [cs.AI]

(or arXiv:2606.01929v2 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2606.01929 Focus to learn more arXiv-issued DOI via DataCite

In Proceedings of the Paris Institute for Advanced Study (Vol. 21) 2026

https://doi.org/10.5281/zenodo.20441584 Focus to learn more DOI(s) linking to related resources

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