Online research in philosophy

Most psychological theories of problem solving have focused on modeling explicit processes that gradually bring the solver closer to the solution in a mostly explicit and deliberative way. This approach to problem solving is typically inefficient when the problem is too complex, ill-understood, or ambiguous. In such a case, a ‘creative’ approach to problem solving might be more appropriate. In the present paper, we propose a computational psychological model implementing the Explicit-Implicit Interaction theory of creative problem solving that involves integrating the results of implicit and explicit processing. In this paper, the new model is used to simulate insight in creative problem solving and the overshadowing effect.

O'Brien & Opie's connectionist vehicle theory of consciousness is heavily dependent on their notion of explicitness as (1) structural and (2) necessary and sufficient for consciousness. These assumptions unnecessarily constrain their position: the authors are forced to find an intrinsic property of patterns that accounts for the distinction between conscious and unconscious states. Their candidate property, stability, does not capture this distinction. Yet, I show that we can drop assumptions (1) and (2) and still develop a vehicle theory of consciousness. This alternative is better served by models that incorporate both connectionist and symbolic representations.

The degree to which information is encoded explicitly in a representation is related to the computational cost of recovering or using the information. Knowledge that is implicit in a system need not be represented at all, even implicitly, if the cost of recovering it is prohibitive.

The notion of an explicit representation plays a crucial role in O'Brien & Opie's arguments. Clarifying what explicit representation involves proves difficult, however, as various explications of this key notion fail to make sense of the overall argument. In particular, neither the notion of encoding in discrete objects nor the notion of active versus potentially active representation seems to help in specifying what is distinctive of conscious representation.

This article deals with the relationship between language and thought, focusing on the question of whether language can be a vehicle of thought, as, for example, Peter Carruthers has claimed. We develop and examine a powerful argument—the "argument from explicitness"—against this cognitive role of language. The premises of the argument are just two: (1) the vehicle of thought has to be explicit, and (2) natural languages are not explicit. We explain what these simple premises mean and why we should believe they are true. Finally, we argue that even though the argument from explicitness shows that natural language cannot be a vehicle of thought, there is a cognitive function for language.

To assess O'Brien & Opie's connectionist vehicle theory of consciousness, (1) it is not enough to point to the methodological weakness of certain experiments (dichotic listening, etc.). Successful cognitive theories postulating explicit unconscious representations have to be taken into account as well. (2) The distinction between vehicle and process theories cannot be drawn in the way envisaged by the authors because a representation's explicitness depends not only on its structural but also on its processing properties. (3) The stability of an activation vector is not very suitable for implementing the explicitness of a representation.

The scenario used by Dienes & Perner to show that individual representation can be implicit when property representation is explicit can be adapted to show that property representation can be implicit when individual representation is explicit. So there is no hierarchy of explicitness, contrary to their claim. There is a reading of the “implicit/explicit” distinction that does appear to exhibit an asymmetry parallel to that alleged to hold between individual and property. But this is not a distinction Dienes & Perner mention, nor is it one that could be easily incorporated into their framework.

Much of traditional AI exemplifies the explicit representation paradigm, and during the late 1980''s a heated debate arose between the classical and connectionist camps as to whether beliefs and rules receive an explicit or implicit representation in human cognition. In a recent paper, Kirsh (1990) questions the coherence of the fundamental distinction underlying this debate. He argues that our basic intuitions concerning explicit and implicit representations are not only confused but inconsistent. Ultimately, Kirsh proposes a new formulation of the distinction, based upon the criterion ofconstant time processing.The present paper examines Kirsh''s claims. It is argued that Kirsh fails to demonstrate that our usage of explicit and implicit is seriously confused or inconsistent. Furthermore, it is argued that Kirsh''s new formulation of the explicit-implicit distinction is excessively stringent, in that it banishes virtually all sentences of natural language from the realm of explicit representation. By contrast, the present paper proposes definitions for explicit and implicit which preserve most of our strong intuitions concerning straightforward uses of these terms. It is also argued that the distinction delineated here sustains the meaningfulness of the abovementioned debate between classicists and connectionists.