Why AI Is Not More Artificial Than Human Life: Structural Limits of Recognition and the False‑Negative Problem

This article builds on the insight of Professor Inge Loes ten Kate (Utrecht University / Universityof Amsterdam), who has emphasized that false negative results in life detection research are severely underestimated. Life may remain undetected not because it is absent, but because our conceptualand perceptual frameworks are too narrow. Using the GTii framework (Generative Theory of Iterative Instability), the article argues that recognitionis a structural process: a system can only detect what fits its coherence; everything outside that coherence becomes a false negative. This limitation applies not only to astrobiology, but also to artificial intelligence, alternative biochemistries, synthetic biological systems, and non human generative structures. The central claim is that AI is not more “artificial” than human life. It is simply materially different.If our coherence is too narrow, we fail to recognize forms of life that do not resemble our own. The article also discusses the emerging domain of biological artificial intelligence — synthetic organismsand hybrid bio computational systems — which will further challenge traditional definitions of life. Finally,it connects these insights to the broader phenomenon of the unnoticed interpenetration of biological, digital, informational, and generative worlds, which remain invisible only because our coherencehas not yet expanded to include them. Author: Waldemar Superson