Predictive processing and the representation wars: a victory for the eliminativist (via fictionalism)

In this paper I argue that, by combining eliminativist and fictionalist approaches toward the sub-personal representational posits of predictive processing, we arrive at an empirically robust and yet metaphysically innocuous cognitive scientific framework. I begin the paper by providing a non-representational account of the five key posits of predictive processing ("prediction-signal", "error-signal", "prior", "likelihood", and "posterior probability"). Then, I motivate a fictionalist approach toward the remaining indispensable representational posits of predictive processing, and explain how representation can play an epistemologically indispensable role within predictive processing explanations without thereby requiring that representation metaphysically exists. Finally, I outline four consequences of accepting this approach and explain why they are beneficial: (1) we arrive at a victory for metaphysical eliminativism in the 'representation wars'; (2) my account fits with extant empirical practice; (3) my account provides guidance for future research; and, (4) my account provides the beginnings of a response to Mark Sprevak's IBE problem for fictionalist approaches toward sub-personal representation.