A Forward-Looking Theory of Content

Abstract

In this essay, I provide a forward-looking naturalized theory of mental content designed to accommodate predictive processing approaches to the mind, which are growing in popularity in philosophy and cognitive science. The view is introduced by relating it to one of the most popular backward-looking teleosemantic theories of mental content, Fred Dretske’s informational teleosemantics. It is argued that such backward-looking views (which locate the grounds of mental content in the agent’s evolutionary or learning history) face a persistent tension between ascribing determinate contents and allowing for the possibility of misrepresentation. A way to address this tension is proposed by grounding content attributions in the agent’s own ability to detect when it has represented the world incorrectly through the assessment of prediction errors—which in turn allows the organism to more successfully represent those contents in the future. This opens up space for misrepresentation, but that space is constrained by the forward-directed epistemic capacities that the agent uses to evaluate and shape its own representational strategies. The payoff of the theory is illustrated by showing how it can be applied to interpretive disagreements over content ascriptions amongst scientists in comparative psychology and ethology. This theory thus provides a framework in which to make content attributions to representations posited by an exciting new family of predictive approaches to cognition, and in so doing addresses persistent tensions with the previous generation of naturalized theories of content.

Representationalism and rationality: why mental representation is real

“…The training system might be sensitive to semantic features if discrepancy detection is implemented accordingly, typically via a cost function, but this isn't always the case. Yet, if the network is constantly updating its values, as seen in predictive coding setups, it could track accuracy information, as recently suggested by Buckner (2022). Moreover, as Buckner argues, sensitivity to error in complex cognitive architectures provides evidence for ascribing determinate contents to subpersonal vehicles (a very similar point is found in Miłkowski 2015).…”