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George Deane

Université de Montréal

Functionalist What matters is the organisation of the processing, not the material

George Deane is a philosopher of cognitive science at the Université de Montréal. His research concerns predictive processing, the framework that treats perception as controlled hallucination constrained by sensory error, and what that framework implies about experience and its distribution across systems. He is a co-author of the Butlin and Long indicator-properties report, the site’s nineteen researcher checklist, where he drafted the analysis of the perceptual-inference indicator, the property covering generative, top-down, and noisy perception modules that higher-order and predictive theories associate with consciousness.

The report’s methodological stance, that AI consciousness should be assessed theory by theory against computational indicators rather than by behavioral vibes, is the position Deane’s broader work defends. His published research on perceptual inference and the epistemic standing of predictive-processing models supplies the conceptual hygiene that assessment programs need when they borrow frameworks from neuroscience and apply them to silicon.

Deane’s profile anchors the predictive-processing wing of the indicator collaboration on this site, alongside the coverage of Anil Seth’s version of the framework and of the same report’s other authors.

Known for. Philosophy of predictive processing, theory-heavy assessment of AI consciousness, perceptual inference and experience, indicator properties collaboration

Coverage on this site

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