Author: gnox

Despite the limitations of computers as models of brain dynamics, models in the form of software that can be run on a computer have advanced the understanding of how the human mind works; see Holland (2003), for example. The ‘Copycat’ model was developed by Douglas Hofstadter and Melanie Mitchell to explore the kind of computations that can come up with creative analogies (Hofstadter and FARG 1995). This program did not try to simulate the human mind or brain as a whole, but instead explored one aspect of human mentality (analogy-making) in a very limited domain, a ‘microworld.’ Copycat comes up with solutions to analogy-making problems, such as this one: ‘I change efg into efw. Can you change ghi in a similar way?’ The program tackles the problem not once but hundreds of times, and the solution it arrives at is not predictable for any specific run. When statistics are compiled on the range of its answers, they often match very closely the statistics on the range of answers that a sample of human subjects arrive at when presented with the same problem. This is the empirical evidence that the way Copycat makes analogies is analogous to the way humans do it. But what makes the discussion of this working model so fascinating is that it provides a fresh context for familiar psychological concepts (such as ‘reifying,’ for instance).

For example, after a thorough explanation of the design principles involved in the model, the authors interpret their own work as follows:

The moral of all this is that in a complex world (even one with the limited complexity of Copycat’s microworld), one never knows in advance what concepts may turn out to be relevant in a given situation. The dilemma underscores the point made earlier: it is important not only to avoid dogmatically open-minded search strategies, which entertain all possibilities equally seriously, but also to avoid dogmatically close-minded search strategies, which in an ironclad way rule out certain possibilities a priori. Copycat opts for a middle way, in which it quite literally takes calculated risks all the time—but the degree of risk-taking is carefully controlled. Of course, taking risks by definition opens up the potential for disaster … But this is the price that must be paid for flexibility and the potential for creativity.

— Hofstadter and FARG (1995, 256)

The implications for human creativity and decision-making (i.e. guidance systems) should be obvious. Principles along these lines could be applied in the realms of communication (see e.g. Sperber and Wilson 1995) and interpretation of texts (see Eco 1990), as well as the ‘economy of research’ (Peirce). Of course, our guidance systems have to guide us through a macroworld, not a microworld, and therefore any models incorporated into them can’t be easily tested in isolation from other components of the system. But such models can certainly simplify the challenge of living and thus reduce the risk of information overload.

We can never compare model with reality (Chapter 9). In a crux, though, we may compare models, and switch from one to another. Thomas Kuhn emphasizes this point with reference to the history of science:

… once it has achieved the status of a paradigm, a scientific theory is declared invalid only if an alternate candidate is available to take its place. No process yet disclosed by the historical study of scientific development at all resembles the methodological stereotype of falsification by direct comparison with nature.… The decision to reject one paradigm is always simultaneously the decision to accept another, and the judgment leading to that decision involves the comparison of both paradigms with nature and with each other.

— Kuhn (1969, 77)

A paradigm or theory can be ‘compared with nature’ only in the sense that the success of its applications can be repeatedly assessed by inductive reasoning based on many observations. Such a ‘comparison’ is indirect, while the comparison of paradigms with each other can be made directly when they are represented iconically.

Likewise, on the individual level, we cannot compare the memory of an event with the event’s occurrence in real time.

… memory is a system property reflecting the effects of context and the associations of the various degenerate circuits capable of yielding a similar output. Thus, each event of memory is dynamic and context-sensitive—it yields a repetition of a mental or physical act that is similar but not identical to previous acts. It is recategorical: it does not replicate an original experience exactly. There is no reason to assume that such a memory is representational in the sense that it stores a static registered code for some act. Instead, it is more fruitfully looked on as a property of degenerate nonlinear interactions in a multidimensional network of neuronal groups. Such interactions allow a non-identical ‘reliving’ of a set of prior acts and events, yet there is often the illusion that one is recalling an event exactly as it happened.

— Edelman (2004, 52)

But such a memory is representational in the semiotic sense; it is even a paradigm of semiosis, as Peirce said: ‘The type of a sign is memory, which takes up the deliverance of past memory and delivers a portion of it to future memory.’

Neither science nor evolution progresses in the sense that we approach omniscience or a state of perfection, but only in the sense that we learn from our mistakes. We progress when we make new mistakes, which we later recognize as such when we learn from them. This – and not any measurable decrease of distance between where we are and some final destination – defines the direction in which we are heading. Learning and evolving would not be possible for an omnipotent and omniscient God, whose acts cannot have unintended consequences.

For humans, the attributes of God can only be idealized human attributes. For instance, we take the human experience of knowing, make it absolute and all-encompassing, and call it omniscience. If we didn’t start from human experience, we would have no idea what these attributes could refer to; but with it, we can imagine a kind of knowing that we know to be far beyond human capacity. We arrive at the concept of omnipotence in a similar way.

We make our God in our own image, then idealize the image by saying that God made us in His image. Our theories about the realm of the divine are likewise maps of our mystical journeys in those realms. Moshe Idel (1988, 29) makes this observation about ‘the theoretical element in Kabbalistic literature’:

Being for the most part a topography of the divine realm, this theoretical literature served more as a map than as speculative description. Maps, as we know, are intended to enable a person to fulfill a journey; for the Kabbalists, the mystical experience was such a journey. Though I cannot assert that every ‘theoretical’ work indeed served such a use, this seems to have been the main purpose of the greatest part of this literature.

The method of trial and error is applied not only by Einstein but, in a more dogmatic fashion, by the amoeba also.

— Popper (1968, 68)

For Popper (1968), ‘the criterion of the scientific status of a theory is its falsifiability, or refutability, or testability’ (48) by means of observations. ‘Thus science must begin with myths, and with the criticism of myths’ (66); ‘we may point out that every statement involves interpretation in the light of theories, and that it is therefore uncertain’ (55n.). ‘To put it more concisely, similarity-for-us is the product of a response involving interpretations (which may be inadequate) and anticipations or expectations (which may never be fulfilled)’ (59). Thus ‘repetition-for-us’ is ‘the result of our propensity to expect regularities and to search for them’ (60).

Observation is always selective. It needs a chosen object, a definite task, an interest, a point of view, a problem. And its description presupposes a descriptive language, with property words; it presupposes similarity and classification, which in their turn presuppose interests, points of view, and problems.

There is no measurement without a theory and no operation which can be satisfactorily described in non-theoretical terms.

— Popper 1968 (61, 82)

Most of the beliefs which actually guide practice, or determine one’s path, are not falsifiable in the way that would qualify them for ‘scientific status.’ Indeed it is doubtful whether any theory outside of the special sciences is falsifiable in that way. For Popper, such enterprises as Freudian psychoanalysis or Marxist dialectical materialism were not sciences but quasi-religions. Peirce had much the same attitude toward the kind of ‘psychical research’ current his day; yet he considered philosophy a science, at least potentially. To do otherwise would block the road of inquiry, which would be even worse than being too credulous.

Antonio Damasio gives an account of the arising of ‘core consciousness’ which maps easily onto the gnoxic meaning-cycle diagram, with emphasis on the automatic, instantaneous and unobservable nature of the process:

Core consciousness is generated in pulselike fashion, for each content of which we are to be conscious. It is the knowledge that materializes when you confront an object [W], construct a neural pattern for it [ception], and discover automatically that the now-salient image of the object is formed in your perspective [M], belongs to you, and that you can even act on it [practice]. You come by this knowledge, this discovery as I prefer to call it, instantly: there is no noticeable process of inference, no out-in-the-daylight logical process that leads you there, and no words at all—there is the image of the thing and, right next to it, is the sensing of its possession by you.

— Damasio (1999, 126)

By the time you are conscious of a phenomenon, its Firstness (quality), Secondness (actuality) and Thirdness (mediation by your ‘perspective’) are already intrinsic to the experience, and only a later abstractive process can distinguish among them as elements of it. Damasio goes on to explain that the time scale of brain events makes them invisible to us. If it takes half a second for the brain to generate a ‘pulse’ of consciousness, then we can’t be immediately conscious of events happening faster than that; we can only model the process and then analyze it as a train of events. The same is true of processes – such as evolution – going on at higher time scales than the human focal level; we can be conscious of them only by theoretical means.

Our models of the world develop through a recursive trial-and-error process, so naturally no step in the process starts “from scratch,” although the whole process must have had a beginning. Each step in an evolutionary, developmental or growth process is represented in our modeling by an experiment on a diagram. Any such process requires continuity with variation: variation without continuity is inconceivable, and continuity without variation is inertia.

Continuity is also … the basis for Peirce’s ‘medieval’ realism with regard to the existence of real universals which refer to natural habits and the continuity of their possible instantiations. But diagrams are intimately connected to symbols, as we have seen, in the diagrammatic reasoning process. Concepts are ‘the living influence upon us of a diagram’ – this should be compared with Peirce’s basic pragmatist meaning maxim, according to which the meaning of a concept is equal to its behavioral consequences in conceivable settings. This implies that signification of a symbol is defined conditionally: ‘Something is x, if that thing behaves in such and such a way under such and such conditions’ – ‘Something is hard, if it is not scratched by a diamond.’ But this maxim, developed on the basis of a conception of scientific experimenting, is formally equal to the idea of diagrammatic experiments: the signification of the concept is the diagram of the experiment. The aim of science is to try to make such conditional definitions as diagrammatic as possible. This is the diagrammatic component in Peirce’s laconic enlightenment maxim, ‘symbols grow’: new symbols arise through diagrammatic experimentation.

— Stjernfelt 2007, 115

Aspects of your internal model make a difference to your practice by functioning as precepts. (This is a version of Peirce’s pragmaticism.) This of course includes your practice of inquiry and reasoning, where precepts guide observation or perception. Peirce explains that the subject of a proposition, which acts like an index in directing attention to some singular object, ‘may be a precept by following which a singular could be found’ (EP2:168; follow this link for context).

A scientific model is one from which testable predictions can be deduced in the form of conditional propositions. Strictly speaking, truth belongs to propositions, not to models. We can test our predictions by comparing them with the results of our experiments, but we cannot compare a sign with its object, a word with its meaning, or a message with its source.

We can’t even compare one model with another, unless some ground of comparison exists which amounts to a more comprehensive model.

It is generally admitted that science is fallible, but often the progress of inquiry is expressed in terms of ‘approximation’ to the truth – as if we could step back and measure how close we were to some absolute reality. This in itself is a model of the process of inquiry, incorporating a more or less mathematical diagram: we imagine ourselves (i.e. our consensus) approaching the truth, in the way that geometrical curve approaches an asymptote (i.e. without ever quite arriving at it).

When a theory works better than previous theories, and has been applied successfully in many situations for a long time, we begin to think of it as a ‘law of nature.’ We have no way of knowing whether some other (as yet unimagined) theory would serve equally well, but if the theory in question seems coherent with other established theories, it gradually becomes integrated into our general model of the world.

The gnoxic meaning-cycle diagram, and Rosen’s diagram of the modeling relation, are diagrams of semiosis, Thirdness and thought in the Peircean sense. As Peirce said (Chapter 10), ‘Thirdness is found wherever one thing brings about a Secondness between two things.’ This follows from Peirce’s highly abstract definitions of the elements of the phaneron:

Firstness is that which is such as it is positively and regardless of anything else.

Secondness is that which is as it is in a second something’s being as it is, regardless of any third.

Thirdness is that whose being consists in its bringing about a secondness.

EP2:267

The ‘something’ or subject in the mode of being called Secondness is as it is in being Second to something else, an Other (but not a significant Other, as significance would be a third). In our gnoxic diagram, W exists as such by virtue of its Secondness to the system or subject to whom it is external; and this Secondness or reactivity is mutual. On the other side of the diagram, M is a ‘model’ by virtue of its dyadic relation to W, a secondness ‘brought about’ by semiosis, the process represented by the arrows in the diagram. But within that process, M can be regarded as a sign which, in its Thirdness or mediation between the subject and its world, brings them into actual relation with each other by directing the actions and attention of the subject (upper arrow), while also being an interpretant of a perceptual sign-complex.

The lower arrow in our diagram represents the action of a ‘natural sign’ in bringing about a subject’s experience of that other subject which is the object of that sign; the Secondness is the experiential relation or ‘reaction’ between those two subjects. The upper arrow represents the action of an intentionally ‘uttered sign’ (Peirce, CP 8.348, EP2:484), or an act of communication directed from one subject (the utterer) to another (the interpreter), which brings about in the latter subject the embodiment of a Form which was already embodied in the former. This ‘embodiment’ or alteration of bodymind is a Secondness brought about by the sign.

Another way of reading the diagram would see the lower arrow as representing the compulsiveness of W’s effect on M in perception, while the upper arrow represents the effect of actual practice on W. Each of these is a Secondness brought about by the function of the guidance system (the modeling relation, the meaning cycle) which governs both ception and practice. In ception, ‘the third is thought in its role as governing Secondness. It brings the information into the mind, or determines the idea and gives it body. It is informing thought, or cognition’ (CP 1.537). In practice, the Thirdness is that of ‘a habit, which determines the suchness of that which may come into existence, when it does come into existence’ (Peirce, EP2:269). This is also the way laws of nature govern what happens in nature – which brings us round to W again.

The Thirdness of a sign determines what kind of relation, or ‘correspondence,’ two things will have:

I define a sign as something, A, which brings something, B, its interpretant, into the same sort of correspondence with something, C, its object, as that in which itself stands to C.

— Peirce, MS L75.235 (1902)

Here B and C are the two things brought into relation by the mediating function of A, the sign. But this ‘bringing into correspondence’ is also a continuous process in which A, B and C are all signs. Within this process, the ‘immediate object which any sign seeks to represent is itself a sign,’ and so is its interpretant; we can analyze the process ad infinitum, giving us ‘two infinite series, the one back toward the object, the other forward toward the interpretant’ (see above). At the limits of these infinite series stand the dynamic object and the final interpretant. At any “point” (or rather any moment) along the way of semiosis, the object and interpretant are immediate.

The term ‘scientific model’ usually refers to conceptual or computer models, not tangible physical structures. One famous episode in science which did involve tangible models was the 1953 discovery by Crick and Watson of the double-helix structure of DNA. Their rod-and-ball constructions, ‘which looked like Tinker Toys gone crazy’ (Depew and Weber 1995, 346), enabled them to ‘scoop’ Rosalyn Franklin, from whom they extracted crucial information leading to the discovery. ‘Unlike Franklin, who would otherwise have been in a good position to deduce DNA’s structure, they were not patient enough to be empiricists’ (Depew and Weber 1995, 345). In other words they used the abductive logic of guess-and-modify rather than the inductive logic of starting with the evidence and methodically building the theory from that ground up; and abductive logic is often facilitated by working with models which are visible (if not tangible). But like all models, the Watson-Crick model greatly simplified the reality, which is far more dynamic, fluctuating at several different time scales (Pagels 1988, 107).

The same is true of anyone’s internal model of the world one has to navigate. When we said in Chapter 3 that ‘map’ is a misleading word because the world in which an animal moves is multidimensional, even that was a gross understatement; see Llinás (2001, Chapter 2) on the ‘dimensionality of the problem of motor control’ (26). In the same chapter, Llinás explains guidance systems in a way quite similar to Varela’s ‘enactive’ model (as outlined in the Chapter 9). ‘The brain’s control of organized movement gave birth to the generation and nature of the mind’ (50); ‘that which we call thinking is the evolutionary internalization of movement’ (35). In the Llinás model, the ‘8-12 Hz rhythmicity of physiological tremor’ (31) acts as the ‘clock’ which enables synchronization of movement. All movement is a modulation of this ever-present ‘tremor,’ which is its material cause; when the organism reacts to external events, sensory input is the efficient cause. But an organism can also initiate movement proactively.

As emphasized in Chapter 10, it should be clear in our reading of the meaning-cycle diagram ‘that the flow from M to W is simultaneous with the flow from W to M. There is only one flow, not two taking turns.’ Within the brain, the functional unity of action and perception is embodied in ‘mirror neurons’ and in the

class of neurons in the frontal lobes called canonical neurons.… Like mirror neurons, each canonical neuron fires during the performance of a specific action such as reaching for a vertical twig or an apple. But the same neuron will also fire at the mere sight of a twig or an apple. In other words, it is as though the abstract property of graspability were being encoded as an intrinsic aspect of the object’s visual shape. The distinction between perception and action exists in our ordinary language, but it is one that the brain evidently doesn’t always respect.

— Ramachandran 2011 (Kindle Locations 938-943)