The Long Now: The Geometry of Consciousness

What is consciousness - and how might we describe it scientifically? Neuroscience can map neural activity with extraordinary detail, yet the relationship between electrical signals and subjective experience remains one of humanity’s most enduring questions.

Mathematician and machine learning researcher Nina Miolane approaches this question from an unexpected direction: geometry. In her work, patterns of neural activity can be understood as structures in a mathematical space. In this view, cognition may be described through the geometry of neural representations: patterns that can be measured, compared, and modeled across biological and artificial systems.

In conversation with science historian Claire Isabel Webb, Miolane explores how new mathematical frameworks may help illuminate long-standing puzzles in the science of mind. If consciousness arises from structured patterns of activity, what does that imply about intelligence? Could similar patterns arise in machine systems? And what might it mean to study consciousness as a phenomenon that admits formal description?

Why This Talk Matters Now

As humanity increasingly shares cognitive labor with machines, a rigorous language for studying the mind would be game-changing. If that language could unlock a deeper understanding of consciousness, it would not only have broad implications for the evolving relationship between human cognition and AI, but for how we as human beings fundamentally understand ourselves.

Dr. Claire Isabel Webb directs the Berggruen Institute’s Future Humans program.

Dr. Nina Miolane is an Assistant Professor at UC Santa Barbara and Director of the Geometric Intelligence Lab.

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