Testable or bust: theoretical lessons for predictive processing

Synthese 200 (6):1-18 (2022)
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The predictive processing account of action, cognition, and perception is one of the most influential approaches to unifying research in cognitive science. However, its promises of grand unification will remain unfulfilled unless the account becomes theoretically robust. In this paper, we focus on empirical commitments of PP, since they are necessary both for its theoretical status to be established and for explanations of individual phenomena to be falsifiable. First, we argue that PP is a varied research tradition, which may employ various kinds of scientific representations, differing in the scope of empirical commitments they entail. Two major perspectives on PP qua cognitive theory may then be distinguished: generalized vs. hierarchical. The first one fails to provide empirical detail, and the latter constrains possible physical implementations. However, we show that even hierarchical PP is insufficiently restrictive to disallow incorrect models and may be adjusted to explain any neurocognitive phenomenon–including non-existent or impossible ones–through flexible adjustments. This renders PP a universal modeling tool with an unrestricted number of degrees of freedom. Therefore, in contrast with declarations of its proponents, it should not be understood as a unifying theoretical perspective, but as a computational framework, possibly informing further theory development in cognitive science.

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Author's Profile

Marcin Miłkowski
Polish Academy of Sciences

References found in this work

Vision.David Marr - 1982 - W. H. Freeman.
The Predictive Mind.Jakob Hohwy - 2013 - Oxford, GB: Oxford University Press UK.
Metaphors we live by.George Lakoff & Mark Johnson - 1980 - Chicago: University of Chicago Press. Edited by Mark Johnson.
Origins of Objectivity.Tyler Burge - 2010 - Oxford, GB: Oxford University Press.

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