This collection examines the philosophical implications of predictive processing (PP), a prominent computational theory of brain function. The central thesis posits that PP, which models the brain as continuously generating predictions about sensory input and updating these predictions based on prediction errors, offers a powerful new lens for understanding consciousness, selfhood, and the nature of reality, challenging traditional philosophical dualisms and materialist assumptions.

The book explores how PP challenges established philosophical concepts like qualia, intentionality, and the unity of consciousness by reframing them within a probabilistic, Bayesian framework. It considers the ethical and metaphysical consequences of a brain operating as a prediction machine, particularly regarding free will, personal identity over time, and the construction of subjective experience. Readers gain a nuanced understanding of how a leading scientific theory of cognition can inform and transform fundamental philosophical debates.

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Key concepts

Predictive Processing — A neuroscientific framework proposing the brain constantly generates predictions about sensory input and minimizes prediction errors.
Prediction Error Minimization — The core computational principle in PP, where the brain adjusts its internal models to better match incoming data.
Bayesian Brain Hypothesis — The idea that the brain operates probabilistically, updating beliefs (predictions) based on new evidence (prediction errors).
Global Workspace Theory — An influential theory of consciousness that can be integrated with or contrasted with PP's mechanisms for conscious awareness.
Phenomenal Consciousness — The subjective, qualitative experience of being, which PP attempts to explain through internal generative models.