HUMAN–AI SCHOLARLY RELIABILITY AND INTERPRETIVE DISTORTION INVESTIGATION

Description Human–AI Scholarly Reliability and Interpretive Distortion Investigation: Consolidated Investigation Report and Current Findings This investigation presents a consolidated observational case study of recurring artificial intelligence errors identified during extended scholarly interactions between independent scholar Yeshayahu Ben-Yehudah and ChatGPT from October 30 through November 4, 2026. The research examines instruction fidelity, interpretive distortion, correction persistence, authorial meaning, conversational redirection, publication-format inconsistencies, and the limitations of AI-assisted self-evaluation. Particular attention is given to instances in which artificial intelligence acknowledged corrections but subsequently repeated errors, substituted unauthorized interpretations, or generated material beyond the researcher's explicit instructions. The investigation incorporates observations arising from scholarly discussions of STILLNESS, ZERO INTENT, SOURCE CONSCIOUSNESS, and the Subject–Witness–Observer framework. These exchanges demonstrate how AI-generated explanations may alter the meaning of a human author's original philosophical inquiry despite repeated clarification. Additional findings document two consecutive instruction deviations on November 4, 2026, involving the unauthorized substitution of a scientific-paper format and the generation of additional material following a corrective statement rather than an instruction. The investigation also records researcher-reported interruptions in ChatGPT access, while distinguishing those observations from unverified technical causes. Central Finding The investigation identifies a recurring distinction between AI-generated coherence and genuine instructional or interpretive fidelity. An artificial intelligence system may produce a grammatically accurate, apparently complete, or corrected response while continuing to misrepresent the human researcher's instructions, observations, or intended meaning. The study also examines the methodological paradox of using an AI system to investigate its own observable failures, particularly when additional errors emerge during that investigation. Scope of the Investigation This research constitutes an independent longitudinal observational case study. Its findings are specific to the documented interactions and do not establish internal software mechanisms, generalized platform failure rates, deliberate interference, or experimentally verified causes of the observed behaviors. The investigation remains open to further examination, correction, and independent scholarly evaluation. Artificial Intelligence Disclosure Artificial intelligence was used to assist with the organization, drafting, consolidation, language refinement, and editorial development of this publication. The original research observations, identification of AI-generated errors, philosophical positions, quotations, and the Ben-Yehudah Six-Pillar Discipline are attributed to Yeshayahu Ben-Yehudah. The artificial intelligence system assisting in preparing this publication is also a subject of the investigation. Its self-assessments do not constitute independent verification of its reliability. Author: Yeshayahu Ben-YehudahInstitution: THE BEN-YEHUDAH INSTITUTEORCID iD: 0009-0002-9256-1093DOI: 10.5281/zenodo.23964497