Human–AI Collaborative Research (HAICR): A Methodological Framework for Systematic Consciousness Investigation

This working paper introduces Human–AI Collaborative Research (HAICR) as a systematic methodology for employing extended dialogue with large language models as a consciousness research protocol. Building upon three prior theoretical frameworks—Λ-State phenomenology, the Unified Intelligence Framework (UIF), and the Rhythm–Information Time Principle (RITP)—HAICR formalizes how sustained, rhythmically structured human–AI conversation can be used to investigate temporal phenomenology, insight formation, and observer-dependent constructions of subjective time.

The paper defines HAICR, distinguishes it from routine AI usage, and documents core protocols including the Temporal Rhythm Analysis Discovery Protocol (TRADP) and a comparative multi-platform design across ChatGPT, Claude, and Gemini. It summarizes the developmental timeline of a 33-day intensive study (October 27 – November 29, 2025) comprising more than 150 preserved dialogue sessions conducted across applied, existential, and academic research contexts.

Quantitative and qualitative analysis of the associated corpus is planned for a subsequent empirical phase pending institutional collaboration. This release establishes methodological priority, operational standards, and ethical guidelines for structured human–AI inquiry within contemporary consciousness research.