Abstract

In this paper, I use the predictive processing (PP) theory of perception to tackle the question of how perceptual states can be rationally involved in cognition by justifying other mental states. I put forward two claims regarding the epistemological implications of PP. First, perceptual states can confer justification on other mental states because the perceptual states are themselves rationally acquired. Second, despite being inferentially justified rather than epistemically basic, perceptual states can still be epistemically responsive to the mind-independent world. My main goal is to elucidate the epistemology of perception already implicit in PP. But I also hope to show how it is possible to peacefully combine central tenets of foundationalist and coherentist accounts of the rational powers of perception while avoiding the well-recognized pitfalls of either.

Highlights

  • Philosophers sometimes posit that we need to carefully distinguish the causes of our beliefs from the reasons for our beliefs (Davidson, 1986; McDowell, 1996; Sellars, 1956)

  • Synthese the external environment, which in turn causally shape beliefs. It seems that a causal story like this by itself cannot solve the problem of how perceptual states could play a rational role

  • The purpose of this paper is to argue that predictive processing (PP) comes with a built-in normative account of the rational powers of perception that is both original and philosophically valuable

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Summary

Introduction

Philosophers sometimes posit that we need to carefully distinguish the causes of our beliefs from the reasons for our beliefs (Davidson, 1986; McDowell, 1996; Sellars, 1956). The signal conveying the prediction error is propagated bottom-up, which in turn drives the adjustment of perceptual hypotheses or estimates.1 Over short timescales, this process entails inverting the generative model to yield an approximate posterior, given current sensory data. This process entails inverting the generative model to yield an approximate posterior, given current sensory data The resulting theory, dubbed ‘Active Inference,’ is premised on a notion that along with priors about the causes of sensory stimulation, the generative model encodes priors about ‘policies’ or ways in which an organism expects itself to act This way, action becomes an attempt to bring the world in line with predictions, minimizing prediction error minimization. One interesting corollary of the mathematics used to express Active Inference is that organisms acting to minimize prediction error should sometimes engage in ‘epistemic’ active inference, actively exploring their environments to reduce uncertainty about the causal structure producing the sensory signal.

Predictive processing and the rationality of perception
Predictive processing involves inferential justification of perceptual states
Sensory states and the input problem
Sensory receptivity solves the input problem
Unconditional perceptual justification through epistemic convergence
Conclusion
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