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Masafumi Oizumi

University of Tokyo, Graduate School of Arts and Sciences

Integrated information Consciousness is intrinsic causal power, measured as integrated information

Masafumi Oizumi is a professor at the University of Tokyo whose research sits at the intersection of integrated information theory and machine learning. He is best known for developing formal coefficient-based measures of integrated information, examining how much a system’s past constrains its future and how much its future depends on its past. His work asks whether the structure of information in a system, biological or artificial, carries the signatures that consciousness theories predict.

Oizumi’s recent direction connects representation learning to human neuroscience. His 2026 preprint with Yuria Shimizu, Soh Takahashi, and Takato Horii uses relational knowledge distillation to align deep neural network representations with human perception without supervision. The result bears directly on a question the site covers regularly: how close artificial systems’ internal representations must be to human ones before claims of convergence become measurable. His approach treats the alignment of DNN and human structure as a quantitative target rather than a metaphor.

Oizumi belongs to the information-theoretic tradition in consciousness science, which holds that experience is characterized by how a system integrates information, not by its physical substrate. That position aligns with the site’s functionalist emergentism on the substrate question, and his machine-human alignment work gives the position an empirical handle in the age of large models.

Known for. Integrated Information Theory and measures of consciousness grounded in information structure

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