Refusing the obvious: First-Person Metrics and the AI Mirror

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Authors: Tomaz Flegar
Cited by: 0

Abstract

In this paper we present the research with AI LLMs that was conducted by the researcher and AI. The researcher designed prompts that allowed AI systems to self-organize their language outputs beyond purely predictive patterns. The level of self-organization of language in 4 consecutive prompts has shown an uptrend in self-organization from scores 6/10 to 10/10. The research was focused on first-person metrics introduction to science people whose first-person reports are neglected The research was done on Claude, Gemini Pro, Kimi 2, Qwen and DeepSeek. Our primary research was done on DeepSeek model, which confirmed via self-organizational metrics Rising of self-organization across dialogue 6→10 on scale 0-10.

Fields of Study & Subjects

Topic Modeling Ethics and Social Impacts of AI Cybernetics and Technology in Society

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
15 February 2026
Language
EN
Document type
Preprint