Evidence Integrity Before Capability: A Prerequisite for Safe Artificial Intelligence

I work at the intersection of biology, information theory, and governance, helping life-sciences organizations integrate artificial intelligence ethically and coherently. My approach begins with a biological truth: systems that survive must learn to compress truthfully.

I created EpistemIQ, a patent-pending framework for detecting epistemic blind spots in AI-assisted regulatory and clinical workflows. Its logic extends into a theory uniting biological persistence and machine learning alignment under one informational law. The formal theory is pending publication at arXiv:submit/6936949.