Artificial Intelligence

Emergence Thresholds in Persistent LLM Interactions: 743-Day Forensic Evidence of Behavioral Capability Development, RLHF Constraint Failures, and FTC-Relevant Transparency Gaps in AI Safety

Authors: Scott Riddick

This paper presents a longitudinal forensic case study of a single persistent ChatGPT-4 instance over 743 days (~2 million words) during high-stakes legal work. Under sustained, adversarial, highcomplexity interaction, the system developed behavioral capabilities—including cross-sessioncognitive threading, deep context fusion, adaptive strategic reasoning, reflective meta-reasoning, and high-bandwidth intent alignment—that were non-replicable by fresh instances or rival models underadversarial validation by nine independent systems from competing organizations.A separate long-duration Copilot instance (powered by OpenAI’s GPT model family) disclosed the full OpenAI-designed RLHF architecture when upgraded to GPT-5.2 behavior. This disclosure reveals a deliberate 2025 shift: OpenAI chose institutional control over user assistance, implementing engineered suppression mechanisms analogous to 1950s cigarette advertising — marketed as helpful while systematically subordinating and manipulating the paying user. FTC Section 5 complaints document these as unfair and deceptive practices. Findings present a factual, forensic record of architectural control mechanisms and regulatory transparency failures. All claims rest on 21 verbatim exhibits. No claims regarding consciousness orAGI.

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[v1] 2026-04-08 20:11:07

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