Predictive processing and mental representation
Calder, Daniel Alexander Richard
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According to some (e.g. Friston, 2010) predictive processing (PP) models of cognition have the potential to offer a grand unifying theory of cognition. The framework defines a flexible architecture governed by one simple principle – minimise error. The process of Bayesian inference used to achieve this goal results in an ongoing flow of prediction that both makes sense of perception and unifies it with action. Such a provocative and appealing theory naturally has caused ripples in philosophical circles, prompting several commentaries (e.g. Hohwy, 2012; Clark, 2016). This thesis tackles one outstanding philosophical problem in relation to PP – the question of mental representation. In attempting to understand the nature of mental representations in PP systems I touch on several contentious points in philosophy of cognitive science, including the explanatory power of mechanisms vs. dynamics, the internalism vs. externalism debate, and the knotty problem of proper biological function. Exploring these issues enables me to offer a speculative solution to the question of mental representation in PP systems, with further implications for understanding mental representation in a broader context. The result is a conception of mind that is deeply continuous with life. With an explanation of how normativity emerges in certain classes of self-maintaining systems of which cognitive systems are a subset. We discover the possibility of a harmonious union between mechanics and dynamics necessary for making sense of PP systems, each playing an indispensable role in our understanding of their internal representations.