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.

The Long View

From Aristotle to Descartes, every generation has recast the mystery of consciousness. A geometric and mathematical explanation might lead to a paradigm shift that could affect all of society's pace layers — how we design, govern, and relate to each other in the next 10,000 years and beyond.

Learn More

• READ “The Fifth Era of Science: Artificial Scientific Intelligence”
• EXPLORE the Geometric Intelligence Lab at UC Santa Barbara
• LEARN how Future Humans at the Berggruen Institute is answering the question “what will life become?”