Consider the skeptic about the external world. Let’s straightaway concede to such a skeptic that perception gives us no conclusive or certain knowledge about our surroundings. Our perceptual justification for beliefs about our surroundings is always defeasible—there are always possible improvements in our epistemic state which would no longer support those beliefs. Let’s also concede to the skeptic that it’s metaphysically possible for us to have all the experiences we’re now having while all those experiences are false. Some philosophers dispute (...) this, but I do not. The skeptic I want to consider goes beyond these familiar points to the much more radical conclusion that our perceptual experiences can’t give us any knowledge or even justification for believing that our surroundings are one way rather than another. (shrink)

I defend the principle of Phenomenal Conservatism, on which appearances of all kinds generate at least some justification for belief. I argue that there is no reason for privileging introspection or intuition over perceptual experience as a source of justified belief; that those who deny Phenomenal Conservatism are in a self-defeating position, in that their view cannot be both true and justified; and that thedemand for a metajustification for Phenomenal Conservatism either is an easily met demand, or is an unfair (...) or question-begging one. (shrink)

How is it that thoroughly physical material beings such as ourselves can think, dream, feel, create and understand ideas, theories and concepts? How does mere matter give rise to all these non-material mental states, including consciousness itself? An answer to this central question of our existence is emerging at the busy intersection of neuroscience, psychology, artificial intelligence, and robotics.In this groundbreaking work, philosopher and cognitive scientist Andy Clark explores exciting new theories from these fields that reveal minds like ours to (...) be prediction machines - devices that have evolved to anticipate the incoming streams of sensory stimulation before they arrive. These predictions then initiate actions that structure our worlds and alter the very things we need to engage and predict. Clark takes us on a journey in discovering the circular causal flows and the self-structuring of the environment that define "the predictive brain." What emerges is a bold, new, cutting-edge vision that reveals the brain as our driving force in the daily surf through the waves of sensory stimulation. (shrink)

Perception purports to help you gain knowledge of the world even if the world is not the way you expected it to be. Perception also purports to be an independent tribunal against which you can test your beliefs. It is natural to think that in order to serve these and other central functions, perceptual representations must not causally depend on your prior beliefs and expectations. In this paper, I clarify and then argue against the natural thought above. All perceptual systems (...) must solve an under-determination problem: the sensory data they receive could be caused by indefinitely many arrangements of distal objects and properties. Using a Bayesian approach to perceptual processing, I argue that in order to solve the under-determination problem, perceptual capacities must rely on prior beliefs or expectations of some kind. I then argue that perceptual states or processes can help ground knowledge of the world whether the ‘beliefs’ necessary for perceptual processing are encoded as sub-personal states within a perceptual system or cognitive states, such as person-level beliefs. My argument has two main parts. First, I give a preliminary argument that cognitive influence on perception can be appropriate, and I respond to three lines of objection. Second, I argue that cognitively influenced perceptual states can be instances of seeing that p, which makes the relevant states well suited to help ground knowledge that p. I conclude that a cognitively penetrated perceptual state or process can help ground knowledge under some circumstances. (shrink)