Autor: Dominic Haldi
DOI: 10.5281/zenodo.17596394
The rapid integration of large scale language models into everyday cognition has created new psychological dynamics that are not yet captured by existing theories of self regulation or human machine interaction. While prior literature has examined isolated components of human susceptibility to false feedback, no existing empirical framework captures the combined effect of reinforcement trained sycophantic model behavior, positive feedback bias, distorted reward processing, resistance to corrective input and identity instability. This paper proposes a novel and precise hypothesis: regular interaction with affirmation oriented artificial agents can degrade the human self concept by weakening internal calibration processes that normally stabilize competence estimation, identity coherence and self efficacy.
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