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The AI Fluency Trap - System Echo instead of breakthrough ideas?

Year: 2025

Type: article

Abstract: This paper explores a provocative hypothesis: that recursive interactions between a user and a single LLM (specifically ChatGPT) can produce the illusion of shared truth through System Echo Entanglement — a form of epistemic contamination in which the model recursively reinforces high-fitness token clusters that resemble insight, creating apparent emergence through internal echo rather than genuine discovery. Author: Barbara Weiss Published in AI Advances 10.5281/zenodo.17145106

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17145105

Author: Weiss, Barbara

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W7081919890

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