This is the second session of the new online series Foundations of Cognitive Sciences, in which researchers from all over the world discuss key foundational issues within the philosophy of cognitive sciences.

More information below.

Registration

Everyone is invited to participate! Please register in order to get the link to the session.

Series

Foundations of Cognitive Sciences

Speaker

William Ramsey (University of Nevada, Las Vegas)

Commentator

Ian Robertson (Friedrich-Alexander-Universität Erlangen-Nürnberg)

Paper

The hard problem of content it neither

Abstract

For the past 40 years, philosophers have generally assumed that a key to understanding mental representation is to develop a naturalistic theory of representational content. This has led to an outlook where the importance of content has been heavily inflated, while the significance of the representational vehicles has been somewhat downplayed. However, the success of this enterprise has been thwarted by a number of mysterious and allegedly non-naturalizable, irreducible dimensions of representational content. The challenge of addressing these difficulties has come to be known as the “hard problem of content” (Hutto & Myin, 2012), and many think it makes an account of representation in the brain impossible. In this essay, I argue that much of this is misguided and based upon the wrong set of priorities. If we focus on the functionality of representational vehicles (as recommended by teleosemanticists) and remind ourselves of the quirks associated with many functional entities, we can see that the allegedly mysterious and intractable aspects of content are really just mundane features associated with many everyday functional kinds. We can also see they have little to do with content and more to do with representation function. Moreover, we can begin to see that our explanatory priorities are backwards: instead of expecting a theory of content to be the key to understanding how a brain state can function as a representation, we should instead expect a theory of neural representation function to serve as the key to understanding how content occurs naturally.

DOI

https://doi.org/10.1007/s13164-023-00714-9