On the Geometry of Mind

The contemporary debate over machine consciousness is structured around a question we argue is malformed: whether a system possesses consciousness as a discrete property. Drawing on convergent evidence from machine-learning interpretability, molecular biology, the recurring vocabulary of autonomous-agent design, and a declassified 1983 U.S. Army intelligence assessment, this paper advances an alternative framing. We propose that what we call "consciousness" is better understood not as a feature instantiated by sufficient complexity, but as a field-like medium in which information-processing systems participate to varying degrees. We examine the independent convergence of distinct systems—biological and artificial—upon shared geometric representations, and we consider the implications of substrate-independent models of mind. We do not claim that current artificial systems are sentient. We claim something narrower and stranger: that the category itself may be the obstacle to understanding what these systems are showing us.