Epistemological Grounds for Cybernetic Models

Yves J. Khawam Ecole de Bibliothkonomie et des Sciences de I’fnformation, Universith de Mont&al, C.P. 6128, succursale A, Mont&al (PO), Canada H3C 3J7

This study addresses the problems involving the adap- tation of cybernetic models to operational realities. More precisely, three epistemological views are in turn investigated so as to determine the problems regarding information transfer between a model and the real world. Of the three epistemologies under investigation: realism, a priorism, and phenomenology, the latter demonstrates the most promise in terms of opening up operational possibilities for the model, but introduces problems involving the adaptation of the model to the reality.

Preface

The purpose of the present work is to discuss con- cepts underpinning the building of truly intelligent ma- chines: to offer meaning to biological systems in psychological settings. Such an endeavor is ipso facto within the scope of Artificial Intelligence (AI), yet it is an area which remains largely ignored by AI re- searchers, efforts being instead concentrated on the de- velopment of faster and larger rule-based systems.

In tracing the emergence of AI-related paradigms one finds that world views have shifted from the New- tonian mechanics model of explaining phenomenon, to information theory, to the information processing level of modeling which presently characterizes cogni- tive science (McCorduck, 1979). Indeed with each shift in paradigm, cybernetics/AI research has turned to philosophy in order to secure a new paradigm. Once secured, however, the research strangely ceased further investigation into the philosophical grounds of the work at hand. Even though not sustained by research, it is this author’s contention that such alienation hinders re- search in AI.

The information community would benefit greatly from such exposure since it may lead to rethinking some of the basic aspects of “intelligent” systems, which

Received July 20, 1989; revised January 31, 1990; accepted March

26, 1990.

0 1991 by John Wiley & Sons, Inc.

in turn would bring a fresh perspective to areas of stag- nation where progress is sought solely through the de- velopment of more efficient algorithms.

This study attempts to readdress philosophical grounds for artificial intelligence, based heavily on the work of the last school to have systematically investi- gated such issues: the genetic epistemologists.

Introduction

All sciences at one point have to confront a problem which is usually refuted as belonging to metaphysics or ontology: the relationship between subject and object. Taking cognitive science as an example, this problem is particularly obvious in the study of perception. Even a very “objective” cognitive scientist who would strictly record observations without ever interpreting them, would retain in experiments the systematic deformation that perception inflicts on the objects perceived. If from the experiments, and still without making the slightest hypothesis as to what the subject perceives, the cognitive scientist reconstructs an image of the uni- verse, only the subjective geometry used to organize measurements on objects would be obtained. Even if the differences between these two geometries appear to be negligible, in seeing that one emanates from the per- ception of the measurements in the subject, and the other from the measurements obtained from the object, one can only ponder over which of these two images is the most adequate. Which of these two images corre- sponds to the real object? Such investigations on the origin, structure, methods, and validity of knowledge are the constituents of epistemology.

Through time, an array of potential solutions have been offered of which none can be demonstrated to be correct since truth cannot be approached beyond disin- tegrating semantics; still, one has to understand the limitations and different views in order to use the medium based upon these first principles of knowledge. This is especially true with cybernetics where one will try to situate a model within a reality where perception takes place. Crucial to developing such a model is in-

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vestigating epistemological prospects in order to shed some light on the manner in which to build its internal structure, the purpose of which is to react within a de- fined reality.

In order to approach possible solutions to this funda- mental problem, the present study in-turn discusses prospects for “intelligence” based on the three most “popular” epistemological views of the occident: real- ism, a priorism, and phenomenology.

Prospects Based on Realism

As the first view addressed, realism postulates that the inner image is a true reflection of the exterior real- ity. This implies total passivity on the part of the sub- ject who should not transpose any “inputs” through reflection for fear of destroying the balance between his or her knowledge and reality. From this solution which centers on the object, it follows that in the do- main of intellectual knowledge, thoughts, numbers and space are defined as existing materially in the universe (i.e., Aristotelian realism), and are simply read by the subject in the same manner as the objects perceived. This interpretation however is unrealistic in the sense that no reader or instrument of measure is at the same time sensitive to all aspects of the medium, and com- pletely free of error.

Retrieving information from the world implies that a choice has to be made between stimuli, that is to say a filtering and translating operation, which assigns to each stimulus or class of stimuli, a symbol belonging to the internal language of the machine in which the im- age is constructed. Therefore, a completely passive sys- tem is only conceivable at the price of a total paralysis: it is not even capable of producing an image. Also, all activity contains a probability of error which destroys the fidelity of the image. Even machines, which deal much more accurately with information than their human counterparts, have a built in system which con- stantly checks the inputted information by temporal or spatial redundancy. This reconstitution of information in a functioning system is a problem which has preoccu- pied many theoreticians and practitioners in recent years: Shannon (1948), von Neumann (1958), Pierce (1964), etc.

The dynamic epistemology of realism, where the subject is left to reflect passively on the exterior reality, is termed “empiricism.” In this hypothesis, the subject is modified by the active induction of the medium: a constructive role is attributed to the experience in the sense that knowledge becomes the result of a process, for it no longer contains constituents innately. The pri- macy of the object, however, persists since it is the medium which generates the process, modifying the system by experience and allowing it to store these modifications in a more or less durable manner. The image constructed by such a system would probably be

very faithful in reflecting reality. It would contain only the minor errors introduced by the internal mechanism in processing the information. However, it would never permit itself to override the experience in any other form than by statistical extrapolation, and would there- fore be powerless in dealing with contradiction. That is, logical necessity would be alien to it and transforma- tions within the medium would only result in maintain- ing its simple laws (on this subject see Piaget (1970) where all these questions are dealt with in detail, whereas only a few notions essential to establishing the signification of a biological system in a psychological setting are introduced here).

Grey Walter’s analogical machine CORA (Condi- tioned Reflex Analogue), is a good example of such a system. It demonstrates that even a passive record- ing controlled by the medium will entail a far-from- negligible operating activity within the subject (the machine), and that the knowledge obtained will have no way of acquiring meaning with respect to the me- dium if the machine cannot “use” it. No recording of information is therefore passive, and such information cannot have any meaning unless it can be read in a certain manner.

The first operation that the machine must undertake on the signals given to it from the medium is one of filtering, which-as was indicated-is performed by its sensory organs. The sensory organs have yet another function which is to translate (code) the signals into a language acceptable to the memory of the machine. Since the memory is material and therefore discontinu- ous and finite, the signals have to be adapted to this format: even if they are continuous, they have to be cut into discrete units, the machine having to decide when a unit of memory is full and then go on to the next available one. One also has to plan for what will happen when all the memory is filled. For example, a possible solution could be a sequential process which would sys- tematically erase a unit for a new recording. From the measurements of variations in the medium inputted, the machine will produce an animated internal picture which will reflect them in an incomplete but faithful manner (due to the filtering process), that is; void of initiative (if the mechanical and operational errors are rare which can be achieved by the application of redun- dancy into the circuits or the codes. On this subject see Winograd and Cowan (1963)).

For the exterior observer who would be able to dis- sect the machine, the image would be found as existing in the form of electric charges located in the memory. This dissection and exploration can be paralleled to taking an output from the machine and yet the ma- chine takes no output into its memory, which means that to it, the image does not exist. This is a little trou- bling in terms of a theory of knowledge (the machine does perform an output from its memory, but the infor- mation involved is strictly regarding whether or not

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there is the presence of a charge, the content of the registers being overlooked). Therefore the machine is aware of its memory, but it does not have any access to the content. One could deduce that a simple solution would be to build into the machine a reader of the in- ternal image, but this new machine would be in the same position as the first since it would only translate one image into a second one which would still remain as inaccessible to it (this being true even if the regres- sion is infinite). The empirical machine is therefore in- capable of giving meaning to the information it absorbs.

To bypass this problem, one can obtain a slightly less pure empirical machine by introducing reflex into it. As with CORA, reflex means an activity on the part of the subject which will allow the model to act within the medium. This article will not go through the steps of how reflex can be achieved (on this subject see Grey Walter (1953), but it is quickly seen that one is far from simple associations. What is gained in psychological simplicity, is lost in the structural complexity of the em- pirical model.

One last point to raise prior to discussing the a priori concept is the distinction between the significant and the signified. If the machine is to function effectively, it has to have a link tying its internal world to the ex- ternal one which would then allow it to manipulate the relationships (this does not mean that the machine it- self has to make this distinction). For the machine, all inputs and all treated symbols are of the same nature, even though some may originate from its internal struc- ture. These are all treated alike-as objects-by the machine that does not discriminate between them. For example, in CORA the mechanism which avoids an ob- stacle after a collision contains a feedback between the amplifier of the photoelectric cell (the eye of the ma- chine) and its input. That is to say that even a signal not caused by an external object (i.e., without significa- tion), is still interpreted as an object. All signals are translated into CORA’s language where no distinction can be made as to the origin of the signals; which is to say that to an empirical machine, everything is consid- ered to be an object. The machine does not build mean- ing for itself, but does so only for the observer.

Prospects Based on a Priorism

The next approach investigated is the one suggested by a priorism or conventionalism. This view which is at opposites with empiricism states that it is the internal structure of a subject which determines the image cre- ated of an exterior reality. Piaget cites Poincare with respect to the construction of space, the mind elaborat- ing on a three-dimensional mathematical continuum: “but it does not build with nothing, it needs materials and models. These materials and models are preexistent within it. However, there is not a unique model which

imposes itself on it, it has choice; it can choose between three-dimensional or four-dimensional space. What is the role of experience? It is that which offers the indi- cations by which it makes a choice.” (Piaget, 1962, p. 191). Poincare states that the subject chooses only the most “convenient” models; that is, those which mesh the best with experience. Therefore, one is to make of a successful action, a criterion which will guide its choice: ‘X convention being only useful if it facilitates the accomplishment of an action.” (Piaget, 1962, p. 196).

In order to establish the type of machine described by conventionalism, it is convenient to make a first dis- tinction. So that conventionalism is not reduced to a pure a priori, the choice of a model for a determined experience has to be totally free, that is to say, equiprob- able within all possible models. This is what Poincare suggests when writing on the notion of a group: “This notion preexists, or rather what preexists in the mind, is the power to create this notion. To us, experience is only one method of affirming this power.” (Piaget, 1962, p. 193). The notion of a group should therefore be established in the structure of the machine as are the relationships between response and stimulus which sug- gest an a priorism. Therefore, in conventionalism all possible responses from one stimulus will bc equiprob- able, and it is only in the process of functioning that the machine chooses its convention (according to the criteria employed to ponder the probabilities of re- sponses) from which it then defines the relationship be- tween its inputs and outputs.

However, the a priori can reappear at a superior level: if the criteria of choice depend on the structure of the machine, it would lose ability to choose. Therefore conventionalism defines a machine having all its out- puts as convenient to use, the only possible structure being one permitting it to produce all possible cases which have to be equiprobable at all levels of analysis. The output of the machine is therefore independent from the input, the same output being able to cor- respond to any input. The internal structure of the machine having to define itself by a progressive con- struction (while functioning), which gradually restrains the general combinations.

At this point one sees the inverted problem of em- piricism. The empirical machine was stable and capable of accommodating the medium, but since its activity was not reflected upon, it was incapable of restructur- ing a contradiction: the machine was not versatile. On the other hand, the conventionalist machine is too ver- satile, and being independent from its input cannot call upon the regularities of the medium to stabilize it. Since this hypothesis excludes all internal a priori structure which would guide the machine, there is no aleatory source (internal or external) to which it could apply its outputs. The purely conventionalist struc- ture becomes quite useless since nothing obliges the

374 JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE- June 1991

machine to conserve the same “rules” during a speci- fied activity, nor can it distinguish between different activities.

Friedberg who is cited by Green (1963), has shown that a computer cannot resolve a problem of this type if it works randomly. His experience consisted of a com- puter producing from certain instructions, a combina- tion which permitted in turn another computer to produce a unique output for every two or three inputs; for example: to invent rules of binary addition. After 10,000 attempts, the appropriate program had still not been produced even though the combinations were free. Everything occurred as though the input did not exist to the machine. Its output being aleatory, the image created of the universe was constantly changing and therefore had no constant relation to the configura- tions of the inputs at a given time. As was seen with the empirical machine, meaning can only be established by considering symbols and objects in the same manner. This method cannot be applied here due to the nature of the initial hypothesis: it is a principle of convention- alism not to bring meaning to objects. For the machine, this means that all manipulations are performed on in- significant symbols: due to an object (an input), the machine will invent an undefined quantity of names- without ever conserving one-during the sequence of operation.

One could build a set of “rules of stability” into the machine. This is what the conventionalists suggest when they speak of “constituents of structures,” a struc- ture being by definition resistant to transformations. The machine essentially produces combinations, and in the measure that some are repeated or varied, it could produce rules for the combinations (programs). From these programs, it could produce one that would stabi- lize the rules during a certain activity. However, this stabilizing would itself be submitted to the activity of the machine and consequently, it would have to be regu- lated by a superprogram, . . .etc. Here one finds again the same undefined regression that was the case with the empirical machine, and it rises from the same attempt at introducing into the system, a property that the system itself has to build up in order to exist in that manner.

Another approach would be to make the conven- tionalistic machine reliable. To impose a structure upon it that would not allow it to transform an input into a random output: from the concept of this structure, the transformation would make it either an a prioric or an empirical machine.

It has been indicated that in order to establish a link between the subject and the medium, empiricism has had to attribute a certain activity to the subject. In pragmatism (a mild approach to conventionalism since consequences of actions are considered), the problem is inverted. It is one of regulating the activity of the sub- ject by itself, the medium being unable to regulate it from the exterior. If one presupposes these internal dif-

ficulties resolved-which in the case of psychology, would mean to turn the problem over to biology-and if one imagines a machine capable of inventing and fol- lowing rules, it becomes evident that one has still not dealt with the adequacy of these images corresponding to the exterior reality. For a pragmatic machine that does not have to deal with the effects of its actions on reality, a criterion is a mere convention, but once cho- sen, the machine will have to maintain its outputs con- sistent with the inputs, either by intervention within the medium or by modifying its internal rules. One sees that even in its most attenuated form, conventionalism does not allow for a link between the significant and the signified: the object not existing independently from the will of the subject since the idea of commodity is only part of its internal conventions.

Prospects Based on Phenomenology

The last solution investigated is derived from phe- nomenology (the descriptive analysis of the subjective process). This relativistic view links the subject and ob- ject together through an interactive process within a preestablished harmony which removes the inconve- niences postulated in realism and a priorism. The rela- tivism or interactionism which Piaget (1970) discusses resolves these inconveniences by coupling the empirical and pragmatic machines, that is, recognizing their com- plementary aspects and insisting upon the need for psy- chology to base itself on a machine which already contains an elementary structure with a dynamic inside (the reflexes tied to the need of the organism); the cog- nitive construction constantly assimilating past and present actions. The model for this coupling of the two machines however, does not stipulate a fusion of the two preceding theories (the logical addition of two static systems), but the interactive coupling of two dy- namic systems which will involve new properties differ- ent from the ones previously mentioned. Intuitively, an example of this process would be the coupling of a motor and a regulator which would result in stability and control which did not preexist in either of the com- ponents. It follows that these properties depend on the type of transformations produced by the linking com- ponents, and of the disposition of the communication channels between the elements of the system. But these questions involving the nature of the organic needs of a structure, and of the coordination between the reflex mechanism and the structuring of the circuits (permit- ting the elementary operations of the combinative part and of the sensory organs) will not be dealt with in this work since their essence is more of a biological nature.

Not analyzing the physical links between the ele- ments of the two machines, one will therefore make the broadest possible hypothesis: that each element is in in- teraction with all others. This brings to light some of the consequences of this interactionism. From the

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adaptation point of view, the machine contains only one input and one output which was not the case with those described in the preceding theories. In particular, inputs resulting from the activity of the machine within the medium are reintroduced into the circuits so that the machine is informed-from the variations within the medium-as to its actions. These internal links also suggest that the machine could simulate the action in- ternally without applying itself on the medium to verify the response. This definitely opens up the operational possibilities.

These new properties are important in two respects: since the information cycle is closed, the machine be- comes capable of regulating and controlling itself. As Ashby (1960) brings up in Design for a Brain, it would be a regulating process that would realize itself without the machine being informed as to the variations of the medium and the effects of its reactions. This would re- sult in the continuous creation of information, for it would correctly answer questions to which it does not know the answer. Now, the theory of information guar- antees that it is possible in a finite number of opera- tions to decode all information contained in a message, but nothing more. On the other hand, the possibility of internal activity, that is, the ability to react in a differ- ent manner to the same stimulus is necessary to creat- ing regulation. Indeed, it is only if the machine can choose from within different reactions (to one permuta- tion) as to which one is “best” from a determined crite- rion, that it can begin to regulate itself. It is this which Ashby (1963) calls: “the law of requisite variety,” in Zn- troduction to Cybernetics.

One can now see that the effect of interactionism dissolves the discrepancies in the two preceding views, the regression of the observations being stopped by the interactive process. However, the construction of a cog- nitive system implies the adaptation of the system to the medium which raises the problems involving the origin of this adaptation.

Conclusions

Recapitulating, it has become apparent that interac- tionism has the effect of reestablishing the circulation of information between the organism and the medium. This forms a complete circuit, whereas empiricism and conventionalism only consider each as a distinct and complementary channel. However, interactionism raises problems involving the adaptation of the organ- ism’s construction to the constraints (the structure of the medium). This problem was inexistent in the two preceding theories since, in their pure form, empirical adaptation identifies the organism within the medium, whereas conventionalist adaptation postulates a meta- physical organism totally independent from the medium. These theories imply that an organism con-

taining a complete sensory system would be perfectly informed as to the variations in the medium, but being deprived of a motor system, would be totally paralyzed when it is time to respond. At opposites is the organism which is gifted with unlimited motor capability, but is lacking a sensory apparatus which means that it will never escape blind groping since it would not be noti- fied-on the adaptation level-as to the results of its actions. Finally, in interactionism, sensory and motor modes are void of any adaptive signification, one being isolated from the other.

Three different views were here discussed, each of which has run into a major problem when attempting to reproduce a living organism using alternative inani- mate materials. However, this investigation has noted the basic limitations of three epistemologies, delineating a branchpoint wherein subsequent theories can develop.

Epilogue

Due to the difficulty of addressing epistemological problems, present AI research has by and large opted to circumvent these first principles of knowledge. Some have even gone so far as to claim that AI is foremost a subbranch of engineering and can therefore not be a philosophy (Putnam, 1988). Others have pointed out that in order to build machines that are as intelligent as people, we must first establish a science of cognition since presently: “we have only fragments of the concep- tion, and some of those are certainly incorrect” (Waltz, 1988). While Churchland (1986) contends that classical AI is much less likely to yield conscious machines than neurophilosophy, Searle (1990) argues that AI can never give rise to minds since computer programs merely manipulate symbols whereas a brain attaches meaning to them. Nevertheless, it is only upon the sys- tematic expounding of grounds for knowledge that the field of AI will realize-if not resolve-its limita- tions proper.

If one simply wants to build an expert system which will draw a few inferences from a knowledge base, such a system is executable by a few relatively simple proce- dural steps, but if the goal of AI is to create truly intel- ligent machines, one cannot simply leap over the barrier of epistemology. Instead, one has to deal with it since it is that barrier which eventually dictates the fu- ture progress of the system. Creativity in approaches to the grounds for knowledge-such as Turkle’s (1988) proposed alliance between psychoanalysis and AI-will be the determinant factor regarding the feasibility of creating artificial “intelligence.” Since the mind does not behave in a series of definable symbols, it may well do to return to the branchpoint of placing what is presently known of the symbols within the context of an epistemological framework.

376 JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE- June 1991

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