This is a follow-on blog to yesterday's on "Visualising Learning Statistically". The most powerful thing in any scientific inquiry is to have two ways of saying similar things. Yesterday, I suggested a way of thinking about learning as emerging distinction-making in terms of relations between normal distributions (in the manner that psychophysicists like Thurstone thought). Among the powerful features of seeing things this way is the fact that the statistics strongly suggests (indeed, insists) that there must be a common origin to the psychological phenomena which produce normal distributions.
Another way of thinking about this is to consider what happens when any phenomenon is presented to consciousness and a distinction is made. A distinction might be called a "category" - something like "chair", "table", "book", "dog". In psychological experiments, what is measured is not the perception of difference per se, but rather the articulation of difference. In psychophysics for example, this is the expression of judgements of degrees of similarity to normality. That entails not only the perception of something in the environment, but selecting a word for it. To utter a word in response to a stimulus is a communicative act.
No word can be uttered without having some idea of the effect of that utterance. We do not make words up for things we don't know. Rather like contemporary machine learning, we fit the word which we know as the most likely utterance which we believe will be understood by others. Unlike machine learning, we might not be sure, so utter the word as a question to see the response, but fundamental we are making a prediction. Paraphrasing George Kelly, who, alongside sociologists like Parsons and later, Luhmann, to make a distinction is to anticipate something in the communication system in which we operate. So we should ask, how might this anticipation work?
To anticipate anything is to recognise a pattern which relates some expected experience to a previous experience. As a pattern, there must be something about a phenomenon which is more general than the specifics of any particular instance. The fact that an anticipation is about something present in relation to something past means that there must be a dimension of time. The time dimension works both in the ongoing unfolding of a present experience, and "backwards" in the sense of reflexivity which relates what is present to what is past. This process of identifying the commonality between what is past and what is present is a selection mechanism for the utterance of whatever one thinks is the category that relates to what is currently seen. To create a selection mechanism for an utterance must entail 1. the selection of an appropriate model of past experience which relates to present experience from a set of possible models; 2. the management of a set of possible models; 3. the ongoing generation of models from present experience.
Yesterday I said that the psychodynamics of distinction-making mean that the ability to refine distinctions is related to the ability to relax distinctions in a different domain - so Freudian "oceanic" experiences are important as an anchor for new distinction-making. That's the kind of statement which might irritate some, but I don't see it as saying anything more than the need for sleep and dreams in order to do work. It is the push and pull of the imagination - much like music, as I wrote here: https://onlinelibrary.wiley.com/doi/full/10.1002/sres.2738
Because making a distinction relies on a selection mechanism which in turn relies on a pattern, we can see a further argument for why the selection mechanism is dynamic between ongoing refinement and "oceanic nothingness". Patterns are segmented typically through repetition. Repetition itself, from an information theoretical perspective, is "redundancy" - it has an entropy of zero. Thus we can say that the segmentation of pattern is achieved through passages of high entropy followed by low or zero entropy. This helps to explain why repetition (as redundancy) is so important for memory - the essential feature of an effective selection mechanism for identifying a category is the ability to segment patterns of experience from the past to relate it to the future.
This also reinforces the point that there must be a common biological origin which is responsible for steering this process. Patterns established in communication rely on cellular communication throughout the brain and other organs in the body. Within cells there are also patterns which reference evolutionary processes which themselves are demarcated by nothing. Statistically this can be observed as a normal distribution, but it can be also modelled as a process of evolutionary construction of patterns which act as selection mechanisms for communication. At a cellular level, these points of "nothingness" are homeostatic points of equilibrium between a cell and its environment.
The role of the environment in learning and evolutionary development is critical. The construction of anticipatory systems is a kind of evolutionary dance of endogenising the environment, where specific stages of development are segmented in ways where one stage can be related to other stages. It is this evolutionary dance which is the reason why there is always a distribution of traits and abilities which then give rise to measurable statistical phenomena.
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