Representation

Interactivism models representation as emergent in a particular kind of biological function, so the first focus is to model the emergence of biological function (2). The normativity of representation derives from that of biological normative function (Bickhard, 1993), and the normativity of biological function derives from certain thermodynamic considerations.

Self-Maintenance and Function

There are two general kinds of stability of patterns of process:

1) Some organizations of process are in energy wells, in the sense that a change in the organization would require the introduction of energy above what is currently impinging on the process. Atoms, molecules, and much of the standard furniture of the world is temporally persisting because of such energy well stabilities.

2) The second form of such stability is that of processes that are far from thermodynamic equilibrium. Such a process will move toward equilibrium, and thus cease to exist, unless some active counterinfluence is operative. Thus, they are open systems of ontological necessity: If cut off from their environments, they cannot remain far-from-equilibrium, and they cease.

In some cases, those influences are completely external to the system itself. A chemical bath can be maintained in a far-from-equilibrium condition, for example, with the pumping into the chamber of appropriate chemicals. Any stability is dependent on the continuing operation of the pumps and availability of the chemicals.

Self-Maintenant Systems. A more interesting case for current purposes, however, is the class of far-from-equilibrium systems that make contributions to their own stability. A canonical example is a candle flame. A candle flame maintains above combustion threshold temperatures; it vaporizes wax into flammable gases; and in standard atmospheric and gravitational conditions it induces convection, which pulls in fresh oxygen and gets rid of waste products. A candle flame is, in several ways, selfmaintenant.

Recursive Self-Maintenance. A self maintenant system can maintain itself over some range of conditions — if a candle is put into a vacuum or doused with water, it ceases. Some systems, however, can, in addition, contribute to their own stability over a range of changes in conditions. They can change what they do to maintain stability in accordance with changes in environmental conditions. A bacterium, for example, might swim and continue swimming if it is going up a sugar gradient, but tumble if it finds itself swimming down a sugar gradient (D. T. Campbell, 1990). It maintains its condition of being self-maintenant in the face of changing environmental conditions: it is recursively self-maintenant (Bickhard, 1993). (For a defense of metaphysical emergence, see Bickhard (2000c, 2003, in preparation)

Function. There is now in place a sufficient model to address both function and representation. Function first: Serving a function is modeled as making a contribution to far-from-equilibrium stability. Serving a function, therefore, is relative to the system which is being contributed to. A heart, for example, may serve a function for a parasite, but be dysfunctional for the host. The normativity of function will be similarly contextualized. Note that serving a function contributes to the stability of a far-fromequilibrium process, which has distinct causal consequences in the world: this is not a model of epiphenomenal function.

The Function of Action Selection and Dynamic Presupposition

A recursively self-maintenant system may just switch from one interaction with its environment to another as differentiated conditions change, such as is the case for the swimming and tumbling of the bacterium, or it may set up indications of multiple interactions that would be appropriate in current circumstances, and engage in some more complicated process of (inter)action selection. That is, action selection can occur via simple triggering, or via more complex selection processes among indicated interaction potentialities.

There is much to be addressed about such systems of action selection, but the crucial point for now is that any triggering of an interaction, or any indication of the current appropriateness of an interaction, presupposes that that interaction is in fact appropriate for the current conditions. Continuing to swim down a sugar gradient is, in general, not appropriate. Appropriateness here is a normative notion, and the normativity is a functional normativity. That is, it is derived from the norm of contributing to the farfrom-equilibrium stability of the system. Interaction (types) will tend to be appropriate in some conditions, and not in others. An indication of the appropriateness of an interaction, therefore, dynamically presupposes that those conditions obtain. The dynamic presuppositions of an interaction or interaction indication are those conditions that would make that interaction appropriate, that render it likely to make a functional contribution. More generally, a process dynamically presupposes whatever those conditions are, internal to the system or external to the system, that support its being functional for the system.

Representation and Content

Representational content. The dynamic presuppositions of a blood circulatory system will in general be internal: hearts and kidneys, for example. The dynamic presuppositions of an interaction indication will be about the environment. If those dynamic presuppositions do not hold, then the interaction will fail. That is, if those dynamic presuppositions are false, the interaction will fail. Interactive dynamic presuppositions, then, can be true or false, and they can be true or false about the environment.

Interactive dynamic presuppositions constitute representational content about the environment. Interaction indications, in this model, are the primitive form of representation. They predicate of the environment that the environment possesses the dynamically presupposed conditions. They predicate that content of the environment.

Such an interactive representation may be false: the dynamically presupposed conditions may not be true. Furthermore, they may be (fallibly) discovered to be false: if the system engages in the indicated interaction, and it does not proceed as indicated, then the dynamic presuppositions, the content, was false, and was falsified. In this model, not only the possibility of error, but also of system-detectable error, are trivially accounted for.

This is indeed a primitive form of representation. More needs to be addressed to indicate its potential to be ground for all representation. It is also a model of representation that has several unfamiliar properties — properties not common in standard models. These too will be outlined.

More Familiar Representations: Objects. I will address first how the interactive model could account for the representation of physical objects. If an organism differentiates a relevant condition in its environment, it will invoke indications of appropriate further interactive potentialities: If a frog differentiates a fly, that differentiation will invoke indications of the possibility of tongue flicking and eating. Even when that differentiation process is inactive, however, the control infrastructure that would engage in it, and its relationships to interaction indications, are still present in the system. Such an aspect of the control structure constitutes a conditionalized indication of interaction potentialities: if XYZ differentiation is made, then QRS interactions will be indicated. Conditionalization, in turn, creates the possibility of iterating such indications: if XYZ differentiation occurs, then QRS is possible, and if QRS occurs, then ABC will be possible (4).

So, interaction indications can both be multiple — they can branch — and they can iterate. As such, they can form webs of interconnected conditionalized indications of interaction potentiality — perhaps vast and complex webs. Some subwebs of such a larger web may come to have special properties. In particular, they may be internally reachable, in the sense that any indicated interaction anywhere in the subweb is reachable as a direct interaction potentiality, perhaps via various intermediary conditional interactions, and that internal reachability property may remain invariant under some relevant class of other kinds of interactions. For example, a child’s toy block will afford multiple potentialities of visual scans and manipulations. Any one of these potentialities is available from any other — e.g., you can always turn the block back so that an earlier visual scan is again possible — so the subweb of interactive potentialities for this block is internally reachable. And that internal reachability itself remains invariant under a large class of other interactions, such as putting the toy away in the toy box, the child leaving the room, and so on. It is not invariant under all possible interactions, however, such as crushing or burning the block.

This outlines the general manner in which the interactive model can scale from simple interaction possibility representations to representations of physical objects. It is a generally Piagetian, or pragmatic (5) model of object representation, and I would suggest a generally Piagetian approach to other more complex kinds of representation, such as abstract representations — such as of numbers (6)

What about Input Processing? Models of representation are standardly what the pragmatists called spectator models. They are models of some homunculus staring back down the input stream, processing inputs, rather than future oriented models of interactive anticipation. But input processing clearly does occur — in sensory systems, for example. If such input processing is not to be taken as somehow constituting or generating representation, what account is to be given of it?

The interactive model distinguishes between two aspects of epistemic relationship to the world: contact and content. Contact with the environment is provided by the differentiations of that environment. Such differentiations are the basis for setting up indications of further interactive potentialities; they are how the system can locate itself in its web of conditional interactive indications. Without contact, no interactive content, no indications of potentiality, would have any likelihood of being appropriate for any particular environment.

Such indications, in turn, constitute representational content. It is such anticipatory indications that involve dynamic presuppositions, presuppositions that can be false. It is in these presuppositions that representation is emergent.

Differentiation in general is generated by the internal outcomes of previous interactions. If an interaction control system is engaged in interaction with an environment, the internal course of that interaction will be partially determined by the control system, but importantly determined by the environment. Differing environments will yield differing internal courses of the interaction, and differing internal outcomes of the interaction. Any particular possible outcome of an interaction serves to differentiate those environments what would yield that outcome from those that would yield a different outcome: the outcomes differentiate types of environments. There is no other information available in such a differentiating outcome per se about what kind of environment it differentiates, but nevertheless it may be useful for setting up indications of further interactive potentialities. If so, then any such indication predicates of that environment whatever properties are dynamically presupposed by those indications. It is the future oriented indications that represent (something about) the differentiated environment, not the differentiations per se.

Differentiations in general may involve full interactions, but a simple version would be a differentiation process that had no outputs, a passive differentiation. A passive differentiation is a differentiation nevertheless, and can serve as the basis for further indications of interactive potentiality.

But passive differentiations are just input processing. Input processing, then, is an aspect of the interactive model just as it is for spectator models. The difference is that standard models take input processing as constituting or generating representation, while the interactive model takes it to be only a simple case of the general function of differentiation — of contact. In effect, input processing models conflate contact and content; they take whatever the contact is in fact with as somehow the content of the purported representation.

Properties of Representation

It is a programmatic task to demonstrate the adequacy of the interactive model for all forms of (purported) representation — perception, memory, rational thought, language, and so on. These have been addressed elsewhere.7 For current purposes, I will take it as demonstrated that the interactive model is a candidate for a model of the nature of representation, and proceed to examine some further aspects of that nature, making a few comparisons with alternative models along the way.

Representational Error. As pointed out earlier, the possibility of representational error is trivially accounted for in the interactive model: the dynamic presuppositions may be false. This is in contrast to correspondence models of representation, that simply do not inherently have the resources to account for error, and must, at best, superimpose some additional criterion for error on the basic correspondence framework. The limitation is, simply, that if a purported representation constituting correspondence exists,then the representation exists and is correct, while if the crucial correspondence does not exist, then the representation does not exist. There are only two model possibilities — the correspondence exists or the correspondence does not exist — but there are three conditions to be modeled — the representation exists and is correct, the representation exists and is false, and the representation does not exist (8).

One attempt to introduce such an error criterion is Fodor’s asymmetric dependency criterion. Consider two conditions under which a representation is invoked, one purportedly correct and the other incorrect. If the representation is constituted simply in the invocation relationship (be it causal, nomological, informational, or whatever), then the purportedly incorrect deployment of the representation is just as legitimate a participant in the representational constitution as is the “correct” object. So, if the objects are X and Y, there are no grounds for the claim that the representation is supposed to represent Xs and that its invocation for Y is in error. Instead, since both Xs and Ys activate the representation, the content should be construed as “X or Y” and the possibility of error evaporates. This so-called “disjunction problem” is just one version of the general problem of accounting for representational error.

Fodor has suggested that the correct and incorrect cases can be distinguished in the following way: the incorrect invocation is dependent on the correct invocation in the sense that the incorrect deployment would never occur if the correct case didn’t exist, but that dependency is not reciprocated; it is asymmetric in the sense that the correct case could occur even if the incorrect case never did. In the by now canonical example, if the COW representation is invoked by a horse on a dark night, that is in error because such “horse on dark night” invocations are asymmetrically dependent on invocations by cows (Fodor, 1990, 1991)

There are multiple problems with Fodor’s model, but a straightforward counterexample to the asymmetric dependency criterion is the following: Consider a neurotransmitter docking on a receptor in a cell surface and evoking corresponding activities in the cell. Here we have full biological and nomological correspondences. Now consider a poison molecule that mimics the neurotransmitter and also docks on that receptor. Here is a clear case of asymmetric dependency, yet at best we have a case of functional error, not representational error. Fodor cannot account for the possibility of representational error (Bickhard, 1993; Levine & Bickhard, 1999)(9).

System-detectable Error. In the interactive model, if an indicated interaction is undertaken and the interaction does not proceed as indicated, then the indication is false, and is falsified for the system itself in a way that is potentially usable by that system. Representational error is system-detectable. Only if error is system-detectable can it be used to guide further behavior or to guide learning processes. Clearly system-detectable error occurs, and, therefore, any model which cannot account for it is impeached.

In general, models of representation do not even address the criterion of systemdetectable error. It is clear, however, that standard models cannot account for it (Bickhard, 1999, 2003, in preparation). No organism can take into account the evolutionary or learning history of its functional representations, or the asymmetric dependencies among potential invocations of its representations, to be able to determine what its representations are supposed to represent. Nor can they then compare that normative content with what is currently being represented to find out if the representation is being truly applied or falsely applied — to accomplish the latter is the problem of representation all over again.

So, if system detectable error is not possible, then error guided behavior and learning are not possible. We know that error guided behavior and learning occur, therefore system detectable error occurs. The model outlined in the text is the only model in the literature that addresses system detectable error. Therefore, it is the only model that can account for a fundamental property of representation, that is not refuted by the fundamental fact of system or organism detections of error.

Furthermore, the core radical skeptical argument is an argument against the possibility of system detectable representational error — we would have to step outside of ourselves to be able to compare our representations with what they purport to represent to be able to detect error in our own representations. This argument has stood for millennia. It is a valid argument, but unsound: it presupposes that the only form of representation is an encoding, past-oriented, form, such as in information semantics. Representation as pragmatically future oriented — interactively anticipatory — transcends the presuppositions of this argument.

Future Orientation. Correspondence models of representation are past oriented, with the input processing spectator looking backwards down the input stream. The interactive model is future oriented. Representation is, most fundamentally, of future potentialities of interaction. Future orientation is a feature of pragmatist models generally, but is rarely found in contemporary models. It is the future orientation of the interactive model that makes accounting for error and for system-detectable error so immediate.

Modality. Interactive representation is of future potentialities of interaction — that is, representation is of possibilities. Interactive representation, then, is inherently modal. Standard models rarely address this issue, but the presumption is that representation is of actualities (whatever is actually on the other end of the input stream) and that modality is something to be added or dealt with later. Interestingly, young children’s’ cognition is inherently modal, with actuality, possibility, and necessity being poorly differentiated, rather than being non-modal with modality developing later (Bickhard, 1988; Piaget, 1987).

Implicitness. Interactive content is the dynamic presuppositions made in indications of interactive potentiality. Those presuppositions are not explicitly represented; instead, they are implicit in the indications themselves. It can be explicit that an interaction of a particular kind, arriving at a designated outcome, indicates that one or more further interactions would be possible, but what supports those indications, what is presupposed about the environment by those indications, is not explicit.

This implicitness of content is fundamentally different from standard models. Encodings cannot be encodings without explicit content. Implicitness is a source of some of the power of the interactive model — for example, I argue elsewhere that the frame problems arise largely from attempting to render implicit content in explicit form (Bickhard, 2001; Bickhard & Terveen, 1995)(11)

The interactive model easily accounts for the possibility of representational error, as well as the possibility of an even stronger criterion: system-detectable representational error. It also has the consequences that representation is future oriented, modal, and, at base, implicit. In all these respects, it differs radically from standard models.

Conclusion

Interactive representation is naturalistically emergent as the solution to the problem of action selection. It is not epiphenomenal, and it emerges naturally in the evolution of biological agents. It has resources with which to model more complex forms of representation. Interactive representation has truth value; it trivially accounts for the possibility of representational error; and it accounts for the possibility of systemdetectable error, and is thus compatible with the facts of error guided behavior and error guided learning. Interactive representation is a candidate for modeling the fundamental nature of representation.

Mark H. Bickhard

References

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Notes

1 An earlier version of this paper was given at Representation in Mind, University of Sydney, Sydney, Australia, June 27-29, 2000, as The Dynamic Emergence of Representation. It is published as Bickhard (2004).

2For a defense of metaphysical emergence, see Bickhard (2000c, 2003, in preparation).

3 It should be noted that, in addressing “serving a function” prior to “having a function”, this explication turns upside down the explicatory organization in etiological models. There are additional fundamentaldifferences. I argue, among other points, that etiological models of function are causally epiphenomenal. See Bickhard (1993, 2003, in preparation).

4 For a more detailed treatment, see (Bickhard, 1993, 2000, 2003, 2004, in preparation; Bickhard & Terveen, 1995).

5 The interactive model is a pragmatic model in the sense of being action based rather than a spectator model (see below), but it is closer to Peirce’s model of meaning as anticipatory habit than to his model of representation per se (Rosenthal, 1983). Anticipations can be false, and can be (fallibly) detected to be false.

6 I characterize these as “generally” Piagetian because, although one of Piaget’s many massive contributions was to construct such action based representations, I don’t think the details of his model are all correct (e.g., Bickhard & Campbell, 1989; Campbell & Bickhard, 1986).

7 E.g., Bickhard, 1980, 1998, 2000b, 2001, in preparation; Bickhard & Campbell, 1992; Bickhard & Richie, 1983; Bickhard & Terveen, 1995; Campbell & Bickhard, 1986.

8 See Millikan (1984) for this point.

9 Millikan (1984, 1993), Dretske (1988), and Cummins (1996) all offer differing ways of accounting for error, which, I argue, all fail (Bickhard, 1993, 1999, 2000, 2003, 2004, in preparation). For reasons of space, I will not develop these arguments here.