We present a theoretical account of implicit and explicit learning in terms of act-r, an integrated architecture of human cognition as a computational supplement to Dienes & Perner's conceptual analysis of knowledge. Explicit learning is explained in act-r by the acquisition of new symbolic knowledge, whereas implicit learning amounts to statistically adjusting subsymbolic quantities associated with that knowledge. We discuss the common foundation of a set of models that are able to explain data gathered in several signature paradigms of implicit learning.

Dienes & Perner present a hierarchical model that addresses the nature – implicit versus explicit – of knowledge in areas as diverse as learning, memory, and visual perception. This framework appears difficult to apply to complex situations, such as those involving implicit learning, because of the indeterminacy that remains regarding knowledge at the low-level in the hierarchy. These reservations should not detract from the positive features of this model. Among its other advantages, it is well adapted to priming phenomena in which the information responsible for the individual's behavior can be precisely defined.

The theoretical framework proposed by Dienes & Perner sets the wrong standards for knowledge to be considered explicit. Animals other than humans possess knowledge, too, some of which is probably explicit. We argue that a comparative approach to investigating knowledge is likely to be more fruitful than one based on linguistic constructs and unobservable phenomena.

This commentary discusses how Dienes & Perner's theory of implicit and explicit knowledge applies to memory research. As currently formulated, their theory does seem to account simultaneously for population dissociations and dissociations between conceptual and perceptual priming tasks. In addition, the specification of four distinct memorial states (correlated with different recognition test responses) faces important methodological challenges.

We argue that Dienes & Perner's (D&P's) proposal needs to specify independent criteria when a subject explicitly represents factuality. This task is complicated by the fact that people typically “tacitly” believe that each of their beliefs is a fact. This problem does not arise for comparative evidence on monkeys, for they presumably lack the capacity to represent factuality explicitly. D&P suggest that explicit visual processing and declarative memory depend on explicit representations of factuality, whereas the analogous implicit processes do not require such representations. Many of the implicit/explicit findings are also found in monkeys, however, and D&P's account needs to explain this striking parallel.

Distinguishing explicit from implicit knowledge on the basis of the active representation of certain propositional attitudes fails to provide an explanation for dissociations in learning performance under implicit and explicit conditions. This suggests an account of implicit and explicit knowledge grounded in the presence of multiple learning mechanisms, and multiple brain systems more generally. A rough outline of a connectionist account of this kind is provided.

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.

Dienes & Perner present a very interesting analysis of two types of knowledge. It is not clear, however, that the words “implicit” and “explicit” are the best basis on which to build a theory of the two types of knowledge. One is also left uncertain as to whether this theory is the best way of ordering the greatest possible amount of relevant data in a way that yields the simplest account possible.

The modernist and scientific juxtaposition of object and subject are inappropriate when investigating the nature of “knowledge.” This commentary argues that the usual methodological dichotomy fails when it is applied to the domain of “knowledge.” The two instead coalesce within the topic itself, demanding the most careful self-awareness.

Some cases of implicit knowledge involve representations of (implicitly) known propositions, but this is not the only important type of implicit knowledge. Chomskian linguistics suggests another model of how humans can know more than is accessible to consciousness. Innate capacities to focus on a small range of possibilities, thereby ignoring many others, need not be grounded by inner representations of any possibilities ignored. This model may apply to many domains where human cognition “fills a gap” between stimuli and judgment.

Early childhood is characterized by many cognitive developmentalists as a period of considerable change with respect to representational format. Dienes & Perner present a potentially viable theory for the stages involved in the increasingly explicit representation of knowledge. However, in our view they fail to map their multi-level system of explicitness onto cognitive developmental changes that occur in the first years of life. Specifically, we question the theory's heuristic value when applied to the development of early mind reading and categorization. We conclude that the authors fail to present evidence that dispels the view that knowledge change in these areas is dichotomous.

This commentary focuses on how Dienes & Perner's (D&P's) claims relate to aspects of development. First, I discuss recent research that supports D&P's claim that anticipatory looking in a false belief task is guided by implicit knowledge. Second, I argue that implicit knowledge may be based on exposure to regularities in the world as D&P argue, but equally, it may sometimes be based on theories that conflict with real world regularities. Third, I discuss Munakata et al.'s notion of graded representations as an alternative to the implicit-explicit distinction in explaining dissociations in infancy.

We applaud Dienes & Perner's efforts while raising some concerns regarding their assimilation of diverse data into a unifying framework. Some of the findings need not fit the framework they suggest. It is also not always clear what, above logico-semantic consistency, assimilation adds to the data that do fit their framework. These concerns are highlighted with reference to their arguments regarding the developmental data and the neuropsychological data, respectively.

Two standard epistemological accounts are conflated in Dienes & Perner's account of knowledge, and this conflation requires the rejection of their four conditions of knowledge. Because their four metarepresentations applied to the explicit-implicit distinction are paired with these conditions, it follows by modus tollens that if the latter are inadequate, then so are the former. Quite simply, their account misses the link between true reasoning and knowledge.

Dienes & Perner propose a theory of implicit and explicit knowledge that is not entirely complete. It does not address many of the empirical issues, nor does it explain the difference between implicit and explicit learning. It does, however, provide a possible unified explanation, as opposed to the more binary theories like the systems and the processing theories of implicit and explicit memory. Furthermore, it is consistent with a theory in which implicit learning is viewed as based on the mechanisms of the cognitive architecture, and explicit learning as strategies that exploit these mechanisms.

We apply Dienes & Perner's (D&P's) framework to the automatic/nonautomatic processing contrast. Our analysis leads to the conclusion that automatic and nonautomatic processing result in representations that have explicit results. We propose equating consciousness with explicitness of aspects rather than with full explicitness as defined by D&P.

Implicit knowledge is perhaps better understood as latent knowledge so that it is readily apparent that it contrasts with explicit knowledge in terms of the form of the knowledge representation, rather than by definition in terms of consciousness or awareness. We argue that as a practical matter any definition of the distinction between implicit and explicit knowledge further involves the notion of control.

Limitations of Dienes & Perner's (D&P's) theory are traced to the assumption that the higher-order thought (HOT) theory of consciousness is true. D&P claim that 18-month-old children are capable of explicitly representing factuality, from which it follows (on D&P's theory) that they are capable of explicitly representing content, attitude, and self. D&P then attempt to explain 3-year-olds' failures on tests of voluntary control such as the dimensional change card sort by suggesting that at this age children cannot represent content and attitude explicitly. We provide a better levels-of-consciousness account for age-related abulic dissociations between knowledge and action.

Dienes & Perner argue that the explicit representation of an individual to which a property is attributed requires explicit representation of the attributed property. The reasons for this conclusion are similar to the reasons why another of their conclusions may be considered suspect: A property may be explicit without an explicit representation of an individual or the predication of the property to an individual. We question the latter conclusion and draw connections to neurophysiological and cognitive evidence.

In this response, we start from first principles, building up our theory to show more precisely what assumptions we do and do not make about the representational nature of implicit and explicit knowledge (in contrast to the target article, where we started our exposition with a description of a fully fledged representational theory of knowledge (RTK). Along the way, we indicate how our analysis does not rely on linguistic representations but it implies that implicit knowledge is causally efficacious; we discuss the relationship between property structure implicitness and conceptual and nonconceptual content; then we consider the factual, fictional, and functional uses of representations and how we go from there to consciousness. Having shown how the basic theory deals with foundational criticisms, we indicate how the theory can elucidate issues that commentators raised in the particular application areas of explicitation, voluntary control, visual perception, memory, development (with discussion on infancy, theory of mind [TOM] and executive control, gestures), and finally models of learning.