Third Edition for Human AI Governance Get the PDF Here Executive Summary HAIA-RECCLIN is an operational methodology for governing AI output through structured human oversight. It comprises two capabilities: Reasoning, a ten-field output format that forces any AI platform to show its work, cite its sources, score its own confidence, flag its own conflicts, and […]
Human Enhancement Quotient
Recursive Language Models Prove the Case for Governed AI Orchestration
MIT built the engine. The question now is who drives. This analysis is written for people designing, deploying, or governing reasoning systems, not just studying them. It is a long-form technical examination intended as a foundational reference for the governance of inference-scaling architectures. In one of the MIT paper’s documented execution traces (see Appendix B […]
The Human Enhancement Quotient (HEQ): Measuring Cognitive Amplification Through AI Collaboration (draft)
The HAIA-RECCLIN Model and my work on Human-AI Collaborative Intelligence are intentionally shared as open drafts. These are not static papers but living frameworks meant to spark dialogue, critique, and co-creation. The goal is to build practical systems for orchestrating multi-AI collaboration with human oversight, and to measure intelligence development over time. I welcome feedback, […]