Gerard O'Brien

Dienes & Perner offer us a theory of explicit and implicit knowledge that promises to systematise a large and diverse body of research in cognitive psychology. Their advertised strategy is to unpack this distinction in terms of explicit and implicit representation. But when one digs deeper one finds the “Higher-Order Thought” theory of consciousness doing much of the work. This reduces both the plausibility and usefulness of their account. We think their strategy is broadly correct, but that consensus on the explicit/implicit knowledge distinction is still a fair way off.

Cognitive science is founded on the conjecture that natural intelligence can be explained in terms of computation. Yet, notoriously, there is no consensus among philosophers of cognitive science as to how computation should be characterised. While there are subtle differences between the various accounts of computation found in the literature, the largest fracture exists between those that unpack computation in semantic terms (and hence view computation as the processing of representations) and those, such as that defended by Chalmers (2011), that cleave towards a purely syntactic formulation (and hence view computation in terms of abstract functional organisation). It will be the main contention of this paper that this dispute arises because contemporary computer science is an amalgam of two different historical traditions, each of which has developed its own proprietary conception of computation. Once these historical trajectories have been properly delineated, and the motivations behind the associated conceptions of computation revealed, it becomes a little clearer which should form the foundation for cognitive science

Reformers urge that representation no longer earns its explanatory keep in cognitive science, and that it is time to discard this troublesome concept. In contrast, we hold that without representation cognitive science is utterly bereft of tools for explaining natural intelligence. In order to defend the latter position, we focus on the explanatory role of representation in computation. We examine how the methods of digital and analog computation are used to model a relatively simple target system, and show that representation plays an in-eliminable explanatory role in both cases. We conclude that, to the extent that biologic systems engage in computation, representation is destined to play an explanatory role in cognitive science.

When it comes to applying computational theory to the problem of phenomenal consciousness, cognitive scientists appear to face a dilemma. The only strategy that seems to be available is one that explains consciousness in terms of special kinds of computational processes. But such theories, while they dominate the field, have counter-intuitive consequences; in particular, they force one to accept that phenomenal experience is composed of information processing effects. For cognitive scientists, therefore, it seems to come down to a choice between a counter-intuitive theory or no theory at all. We offer a way out of this dilemma. We argue that the computational theory of mind doesn't force cognitive scientists to explain consciousness in terms of computational processes, as there is an alternative strategy available: one that focuses on the representational vehicles that encode information in the brain. This alternative approach to consciousness allows us to do justice to the standard intuitions about phenomenal experience, yet remain within the confines of cognitive science