Synthetonia: Tonal Strain as a Candidate Facet of AI Fatigue

AI fatigue is no longer unstudied, but existing scales measure interaction cost: volume of generated output, the burden of verification, and prompt iteration. Synthetonia isolates a distinct source of strain: tonal sychronicity and register-level satiation caused by prolonged exposure to hyper-optimized, low-variance conversational AI prose. This position paper defines Synthetonia, articulates its theoretical grounding in stimulus habituation and affective flattening, and situates it alongside concurrent fatigue frameworks and historical psychological strain constructs (such as the Uncanny Valley, Technostress, and Zoom Fatigue). It outlines a clear empirical agenda—including scale development, between-subjects experiments, and transcript analysis—designed to test the construct's discriminant validity. This record includes the manuscript PDF.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-06
DOI
https://doi.org/10.5281/zenodo.22566310
Primary Topic
Emotion and Mood Recognition
Type
preprint
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preprint

Synthetonia: Tonal Strain as a Candidate Facet of AI Fatigue

Dana Lloyd Texiera
Zenodo (CERN European Organization for Nuclear Research)
Emotion and Mood Recognition
preprint

Synthetonia: Tonal Strain as a Candidate Facet of AI Fatigue

Dana Lloyd Texiera
preprint en

Abstract

AI fatigue is no longer unstudied, but existing scales measure interaction cost: volume of generated output, the burden of verification, and prompt iteration. Synthetonia isolates a distinct source of strain: tonal sychronicity and register-level satiation caused by prolonged exposure to hyper-optimized, low-variance conversational AI prose. This position paper defines Synthetonia, articulates its theoretical grounding in stimulus habituation and affective flattening, and situates it alongside concurrent fatigue frameworks and historical psychological strain constructs (such as the Uncanny Valley, Technostress, and Zoom Fatigue). It outlines a clear empirical agenda—including scale development, between-subjects experiments, and transcript analysis—designed to test the construct's discriminant validity. This record includes the manuscript PDF.

Zenodo (CERN European Organization for Nuclear Research)
Reduced inequalities
Emotion and Mood Recognition
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