Mark Bickhard

This article focuses on the problem of representational content. Accounting for representational content is the central issue in contemporary naturalism: it is the major remaining task facing a naturalistic conception of the world. Representational content is also the central barrier to contemporary cognitive science and artificial intelligence: it is not possible to understand representation in animals nor to construct machines with genuine representation given current (lack of) understanding of what representation is. An elaborated critique is offered to current approaches to representation, arguing that the basic underlying approach is, at root, logically incoherent, and, thus, that standard approaches are doomed to failure. An alternative model of representation - interactivism - is presented that avoids or solves the problems facing standard approaches. Interactivism is framed by a version of functionalism, and a naturalization of that functionalism completes an outline of a naturalization of representation and representational content.

I will argue that mechanism is not sufficient to capture representation, thus cognition. More generally, mechanism is not sufficient to capture normativity of any sort. I will also outline a model of emergent normativity, representational normativity in particular, and show how it transcends these limitations of mechanism. To begin, I will address some illustrative attempts to model representation within mechanistically naturalistic frameworks, first rather generally, and then in the cases of the models of Fodor and Millikan.

Information and representation are thought to be intimately related. Representation, in fact, is commonly considered to be a special kind of information. It must be a _special_ kind, because otherwise all of the myriad instances of informational relationships in the universe would be representational -- some restrictions must be placed on informational relationships in order to refine the vast set into those that are truly representational. I will argue that information in this general sense is important to genuine agents, but that it is a blind alley with regard to the attempt to understand representation. On the other hand, I will also argue that a different, quite non-standard, form of information is central to genuine representation. First I turn to some of the reasons why information as usually considered is the wrong category for understanding representation; second to an alternative model of representation -- one that is naturally emergent in autonomous agents, and that does involve information, but not in any standard form; and third I return to standard notions of informational relationships and show what they are in fact useful for.

The interactivist approach to development generates a framework of types of constraints on what can be constructed. The four constraint types are based on: (1) what the constructed systems are about; (2) the representational relationship itself; (3) the nature of the systems being constructed; and (4) the process of construction itself. We give illustrations of each constraint type. Any developmental theory needs to acknowledge all four types of constraint; however, some current theories conflate different types of constraint, or rely on a single constraint type to explicate development. Such theories will be inherently unable to explain important aspects of development.

I will argue that social ontology is constituted as hierarchical and interlocking conventions of multifarious kinds. Convention, in turn, is modeled in a manner derived from that of David K. Lewis. Convention is usually held to be inadequate for models of social ontologies, with one primary reason being that there seems to be no place for normativity. I argue that two related changes are required in the basic modeling framework in order to address this (and other) issue(s): (1) a shift to an intentional model—among other reasons, in order to account for normativity—and (2) moving away from the belief-desire, propositional attitude, framework for understanding the intentional realm toward an interactive, pragmatic model of intentionality. These shifts provide natural approaches to: (1) understanding the normativities of social realities; (2) the sense in which social ontology is often constituted in implicit relations among the participants rather than elaborated and iterated explicit beliefs and desires; (3) and language.

Emergence seems necessary for any naturalistic account of the world — none of our familiar world existed at the time of the Big Bang, and it does now — and normative emergence is necessary for any naturalistic account of biology and mind — mental phenomena, such as representation, learning, rationality, and so on, are normative. But Jaegwon Kim’s argument appears to render causally efficacious emergence impossible, and Hume’s argument appears to render normative emergence impossible, and, in its general form, it precludes any emergence at all. I argue that both of these barriers can be overcome, and, in fact, that they each constitute reductios of their respective underlying presuppositions. In particular, causally efficacious ontological emergence can be modeled, but only within a process metaphysics, thus avoiding Kim’s argument, and by making use of non-abbreviatory forms of definition, thus avoiding Hume’s argument. I illustrate these points with models of the emergent nature of normative function and of representation.

The dominant assumptions -- throughout contemporary philosophy, psychology, cognitive science, and artificial intelligence -- about the ontology underlying intentionality, and its core of representationality, is that of encodings -- some sort of informational or correspondence or covariation relationship between the represented and its representation that constitutes that representational relationship. There are many disagreements concerning details and implementations, and even some suggestions about claimed alternative ontologies, such as connectionism (though none that escape what I argue is the fundamental flaw in these dominant approaches). One assumption that seems to be held by all, however, usually without explication or defense, is that there is _one_ singular underlying ontology to representationality. In this paper, I argue that there are in fact quite a number of ontologies that manifest representationality -- levels of representationality -- and that _none_ of them are the standard "manipulations of encoded symbols" ontology, nor any other variation on the informational approach to representation. Collectively, these multiple representational ontologies constitute a framework for cognition, whether natural or artificial.

Function emerges in certain kinds of far-from-equilibrium systems. One important kind of function is that of interactive anticipation, an adaptedness to temporal complexity. Interactive anticipation is the locus of the emergence of normative representational content, and, thus, of representation in general: interactive anticipation is the naturalistic core of the evolution of cognition. Higher forms of such anticipation are involved in the subsequent macro-evolutionary sequence of learning, emotions, and reflexive consciousness.

The variation and selection form of explanationcan be prescinded from the evolutionary biologyhome ground in which it was discovered and forwhich it has been most developed. When this isdone, variation and selection explanations arefound to have potential application to a widerange of phenomena, far beyond the classicalbiological ground and the contemporaryextensions into epistemological domains. Itappears as the form of explanation most suitedto phenomena of fit. It is also found toparticipate in multiple interestingrelationships with other forms of explanation. We proceed with an examination of multiplekinds of phenomena, interrelationships withother members of the family of forms ofexplanation, and some novel applications evenwithin the home ground of evolutionary biology.