Title: VET: A Framework for Analyzing AI Discourse

Original: arXiv:2606.01929v1 Announce Type: new

Abstract: The general public’s understanding of AI is increasingly at risk due to the polarization of AI discussions in both traditional and social media, where extreme viewpoints threaten AI Literacy. To address this, this paper presents the VET Framework, a classification system that evaluates AI discourse based on three dimensions: valence, effectiveness, and trajectory. The study demonstrates how this framework facilitates the identification, comparison, and critical assessment of four dominant narratives: AI Normalcy, AI Denial, AI Doom, and AI Hype. Through the lens of VET, the analysis reveals how each of these perspectives tends to overemphasize specific features of AI’s current status or future development. Ultimately, the paper illustrates how the VET framework functions as a practical AI Literacy resource by enabling the rigorous "vetting" of highly polarized AI debates.

Source: arXiv Generated at: 2026-06-02 00:00:00 UTC