Sunday, 2 October 2022

Sleeping and Learning

If learning is about making new distinctions, there is a question about how we know a distinction. Since all distinctions have two sides (an inside and an outside) our knowledge of a new distinction must be able to apprehend both sides of it. So we must be able to cross the thresholds of our distinctions. At the same time, if we are not inside our distinctions - if we are not able to use them as a lens to view the world - they are useless in a practical way. Yet the distinctions which make up our lens are dependent on our being able to cross their threshold and see no distinctions. Is this sleep and dreaming?

We don't understand why we sleep. Except that we know that if we don't sleep, we die. That suggests that it is not just our conscious distinctions that require stepping outside of themselves, but the  physiological distinctions between cells, organs, etc. If they break down, we're dead. 

At the same time, we know - at least anecdotally - that we learn in our sleep. We wake up in the morning having not been able to do something the day before, and find ourselves improved in our performance. Possibly because we've got "more energy" - but what's that? Thinking about distinctions necessitating boundary crossing helps here.

The Freudian "primary process" is the dream world of no distinctions. The world of the new baby. The "secondary process" is the regulating filter which channels the energy from the primary process into useful distinctions which (for adults at least) are conditioned by the social conventions of the "superego". (Talcott Parsons correctly recognised that Freud's superego was sociological). More to the point, this psychodynamic process between ego, id and superego was continual: a kind of pulse between the "oceanic" primary process and the secondary process. 

In education, the superego rules, and technology has ensured that its grip on the imagination of staff and students has become every more brutal. But technology outside education stimulates and suppresses the id: from cat videos to shopping to porn, we can inhabit a simulated oceanic state. Only in sleep itself is there some contact with the reality of the id.  

What have we missed in the way that we think about learning? When we examine our metrics for competency, our "constructive alignments", assessment schemes, etc, we seem to have assumed that the distinctions of learning are fixed: once we learning something it stays there. In conscious experience this looks like a sensible proposition. But to assume this misses the possibility that our distinctions appear persistent precisely because they result from a dynamic process of distinction and undistinction. 

To be clearer about this, the deepest encounter with the oceanic experience comes through an intersubjective acknowledgement of uncertainty. That can be the best teaching - not the delivery of content, or the forcing of distinctions written in textbooks, but the revealing of understanding by a teacher to the point of revealing of uncertainty. "I'm not sure what this means - what do you think?"

I've written about this kind of thing here: Digitalization and Uncertainty in the University: Coherence and Collegiality Through a Metacurriculum (springer.com), and this last week I got a further reminder of the importance of this approach in an EU project which Danielle Hagood and I led around digitalization. In both cases, technology was the stimulus for uncertainty and dialogue. It is the technology which takes us to the oceanic state, from where (and this was quite obvious in my EU project) new distinctions and new thinking emerges. 

The dialogical is the closest thing we have to the primary process in education - it is rather like music because it connects us to more fundamental mechanisms. John Torday suggested in conversation last week that in sleep our cells realign themselves with their evolutionary origins, effectively connecting our waking thoughts (what Bohm calls the "explicate order") with fundamental nature ("implicate order"). That's a wild idea - but I quite like it!

Wednesday, 21 September 2022

About Learning and de-growth

Seymour Papert argued that we do not have a word for the art of learning in the same way that we have words for the art of teaching (pedagogy, didactics) (see his "A word for learning": http://ccl.northwestern.edu/constructionism/2012LS452/assignments/2/wordforlearning.9-24.pdf). Papert then suggests the word "mathetics", drawing attention to the fact that "mathematics" appropriated the word for learning to refer to its specialised practices, when the word "Mathematikos" simply meant "disposed to learn". There may be deeper things to explore in this etymological relationship. 

We tend to think of learning as a kind of growth. As we learn, we know "more stuff", we gain "more knowledge", and we might even imagine that we get bigger heads! Babies start small and get bigger (up to a point), and as they get bigger they learn. Learning produces material artefacts which certainly do increase in size - before the internet, knowing more stuff meant more books, and (perhaps) a bigger library (to display as our zoom background!). The bigger the library the cleverer the people.

I was listening to Neil Selwyn talking about "de-growth" as a possible response to climate change and thinking about how education might support this (here: https://media.ed.ac.uk/playlist/dedicated/79280571/1_6u9a41zh/1_l7anxlgx). Crudely, we imagine that our ecological crisis is caused because things have grown too big, and that to address it, we need to "degrow". But what do we mean by "big" or even "growth"? My favourite source for thinking about this is Illich's "Tools for Conviviality". He talks about the outsized growth of technology and institutions beginning as beneficent, and becoming malevolent. The causes for the transition from beneficence to malevolence are mysterious - they may lie in our physiology and evolutionary biology (that's another post). But the actual manifestation of pathology is not size - it is a reduction in variety. Illich's clearest example is 100 shovels and 100 people digging a hole, which is eventually replaced by one person and a JCB. Which has the greater variety? The loss of variety as the technology becomes more powerful results in an increase in the creation of scarcity - and the "regimes of scarcity" are the ultimate propellent for positive feedback loops and accelerating crisis. 

The ecological crisis is a crisis resulting from the loss of variety caused by modern living, and within modern living, we must include education. No human institution excels in the art of producing scarcity more than education. The rocket fuel for the rest of the ecological crisis lies at the classroom door. But we can't seem to help ourselves. We see education as the solution to our troubles, not the cause! Education will teach us to "de-grow"... quick! roll-up for "degrowth 101"! Why do we do this? It is because we mistake education for learning. 

We tend not to see learning but instead see "education" in the same way that we tend not to see health but instead see "health systems". "Education" (and "health systems") get bigger and more powerful - rather like the library which forms part of educational institutions. As they get bigger and more powerful they lose variety (look at the NHS today). But "learning" (and "health") do not grow or get bigger. Both of these terms refer to processes which relate an organism (a person, a community, an institution) with its environment. These terms relate to the capacity of any organism to maintain their viability within their environment - indeed "health" and "learning" are deeply connected concepts. Learning is not about growth, but about homeostasis. 

Having said this, it's obvious that as we get older, we learn more stuff, we can do more things, we talk to more people, and so on. But we are really in a continual process of communion with a changing environment. Babies may seem to learn to scream to get attention, but their physiological context is changing alongside an epigenetic environment within which what it is to remain viable is a continual moving target. The education system appears to be a way of forcing certain kinds of environmental change, and as a result insisting on certain physiological responses (which appear to reproduce regimes of scarcity, and social inequality). Indeed, what we call "growth" is an outward manifestation of an unfolding of physiological potential in a changing environment. If growth was as fundamental as the "de-growth" people say, why does anything stop growing?

So if learning is not about growth, but about the viability of an organism in an environment, how can we visualise it differently? One way is to think about it mathematically - and so to draw back to the origin of the word for mathematics, mathematikos and "mathetic". If learning is a process of variety management, and a developing environment has differing levels of variety (and indeed, increasing entropy), then learning is really a process of finding a kind of resonance with that environment. These orders of variety and variety management might be rather like orders of prime numbers, or different levels of scale in a fractal, or different orders of infinity. Mathematically, we might be able to see learning in geometrical forms produced through cymatic patterns:

or knot topologies, 

Or Fourier analysis, or even in Stafford Beer's syntegrity Icosahedron (see Beer's book "Beyond Dispute" https://edisciplinas.usp.br/pluginfile.php/3355083/mod_resource/content/1/Stafford%20Beer_Beyond%20Dispute.pdf):

These forms are expressions of relations, not quantifications of size. If we see size (and growth) as the problem we don't only miss the point, but we feed the pathology. 

We urgently need a more scientific approach to learning. We are going to need our technologies to achieve this. This is not ed-tech, but technology that is necessary to help us understand the nature of relationship. I fear that for those consumed with ed-tech, blaming it for the demise of "education", a different kind of approach to technology and a more scientific approach to learning is not a thinkable thought. 

I feel the need to make this thinkable is now very important. 




Monday, 19 September 2022

Rethinking Education and a "Trope Recognition Machine"

I went to a conference at the weekend on "Rethinking Education". As is often the case with these things, there were some good people there and some good intentions. But I came away rather depressed. It's often said that there is nothing new in education, and events like this prove it. What it amounted to was a series of tropes uttered by various people, some of whom were aware that they were tropes, and others who genuinely thought they were saying something new. Meanwhile the system trundles on doing its thing - and while everyone there might admit that the thing it does is not very good, there is a surprising lack on clarity on what the system actually does. 

When we ask people to rethink something, it is often framed as an invitation to think about the future - to say, "let's bracket-out the system we have, and conceive of the system we want". But this is naive because the system we want is always framed by the system we are in, and it is always difficult to see the frame we are in, and what it does to our thinking. Frame-blindness has specific effects - one of which is the tropes.

At one point I was getting a bit frustrated by the degree of repetition in the tropes that a wicked thought occurred to me: what if we had a trope recognition machine? What if there was some device that could process all the utterances and classify them according to their trope identity. And of course, current machine learning is very good at this kind of job. But if you had a trope recognition machine, what use might it be? 

If we look at "rethinking education" as a problem situation - not the problem of "rethinking education" but the problem of talking about "rethinking education" - this problem is one of time-consuming redundancy of utterances. Basically many people say the same thing, and feel the need to say the same thing. Indeed, I suspect meetings like this owe their appeal to the opportunity they present to people to say what's in their heads in the confidence that what they say will "resonate" with what else is said. In other words, the redundancy is there in the desire to attend and speak in the first place. Perhaps we need to think about this - about the dynamic of redundancy in communication. 

One of the most interesting things about redundancy is how attractive it seems to be - it is after all about pattern, and patterns are what we look for when we try to make sense of something. So if we want to make sense of education, we need to go somewhere where we can fit into a pattern - a conference. But this is curious because the motivation of most people at conferences is to "get noticed" - to have their version of a trope which is distinct that everyone looks to them as some kind of originator of something which has been said before (actually the whole academic discourse is like this, but let's not go there!). So how does that work? How does the desire for collective sense-making through pattern and egomania fit together?

I've been reading Elias Canetti's "Crowds and Power" and I think there is something in there about this tension between the search for redundancy and pattern, and the expression of the ego. Canetti sees the individual as someone who wants to preserve the boundary of their self. They don't even want to touched by someone else most of the time. And yet, they also want to belong to the crowd. Although Canetti was opposed to Freudian psychodynamics, clearly his analysis of the crowd is treading similar territory to psychodynamics: the crowd is the Freudian super-ego. 

The search for redundancy in going to conferences and saying similar things to everyone else is crowd-like behaviour. It seems to be driven by egos who want to get noticed - to preserve and reinforce their boundary of the self. 

I think the best way to think about this is to see both the ego and the superego as essentially dealing with contingency. They have to find a way to maintain a balance between their internal contingency and the external contingency. That means that it is necessary to understand and control the external contingency. Creating redundancy through utterances is a way of establishing some degree of control over external contingency: it is a way of establishing a "niche" in which to survive (my favourite example of an organism using redundancy to create a niche is a spider spinning a web). 

What is discovered about the external contingency has an effect on internal contingency. The ego is troubled by the subconscious, which contains the vestiges of experience and desire from infancy - and the legacy of education. The ego is satisfied with the niche it creates in talking about education and feels more secure. (What appears as egomania may simply be a need to establish some kind of inside/outside balance). But as a result, conferences like this actually satisfy the psychodynamic needs of individuals struggling in a terrible system for a short time. They are essentially palliative. 

Understanding these dynamics at conferences may be a first step to remedying the problems in the education system itself. A trope-recognition machine could pinpoint the different positions and contingencies which are expressed in a group: it could highlight areas of deep contention and uncertainty and thus focus discussion on those issues, codifying the underlying patterns that everyone is searching for in a way which could save a lot of time and frustration. That might result in some better decision-making perhaps.

Monday, 5 September 2022

Learning and the Redshift of Biology

When we think we observe learning happening in others, we think of a change in an individual. We see each individual as on some kind of trajectory along a path which we have determined through making prior observations throughout history. This is encoded in our formal processes of education. In each individual we observe, there is a wide range of variation in this trajectory. Some lead to "success", some lead to "failure". One of the tragedies of education is that there is never enough time, nor the energy, to look at an individual's learning really closely. Perhaps parents (sometimes) and psychotherapists get a bit closer. Scientists observe ecosystems, stars, and cells with far more intellectual curiosity and desire for precision.

Learning never happens in "others". It happens in relationships - and those relationships inevitably include anyone who wants to "observe". If we imagine that in any relational situation, there are "engrams" - structures in consciousness - and "exterograms" - externally observable phenomena, the only observable aspect of relationship are the exterograms of communication - we can at least write spoken words down, record actions, assess, etc. In education research, this is basically what is done, and these "exterograms" of the learning process are subjected to various kinds of analysis which produce conclusions like "phonics helps children to read", or "people have different (codifiable) learning styles", and other such stuff. These are really political statements about which there is endless debate. Good for the champions of phonics and learning styles - after all, "there's only one thing worse than being talked about..."

The phrases "exterograms" and "engrams" were suggested by Rom Harré as a way of introducing the problems addressed by his "positioning theory". Harré said something very sensible about learning: "you know when learning has happened because the positioning changes". This seems true - the transition from apprentice to master is precisely a change in positioning between master and apprentice. This suggests to me that rather than look at the trajectory of an individual, we should look at the trajectory of positions. 

How could education become focused on the trajectory of positions, rather than the trajectory of individuals? Perhaps a good place to start in thinking about this is how an "individual" focus of education is different from a position-focused education. The former is built around the material consumption and production of students - textbooks, lectures, essays, exams, etc. The latter is built around the energy of communication between people. Is the shift one from a focus on matter to one on energy? 

In an energy oriented focus, there are no "exterograms" really. They are mere manifestations of energy in the learner (or lack of it!). In a dialogical relation, these exterograms have an effect on others in causing the production of other communications. But in the process, there is a  physiological background which is where the thinking and adaptation takes place. These physiological processes obey rules about which we have little understanding - but where an increasing amount of biological evidence is suggesting we might have new and highly productive scientific paths to tread. 

We are all made from the same stuff, and all our stuff - our cells - comes from a point source - a unicell. Through evolutionary history, cells diversified and acquired (through endogenisation of aspects of their historical environment) various features (mitochondria) which we find in us and everywhere else in nature. There is a surprising lack of variety of cell types in the human body - only about 200. Our learning processes are processes of cellular communication - not just within us, but between us. Those processes of communication reference the origins of cells - shared cellular history is a deep coordination mechanism which underpins what we might call "instinct". Instincts arise from cellular relations, just as learning arises from human relations. The same processes are in operation at different orders of scale. 

Looking at learning as the trajectory of "positions" in relations is like looking through the James Webb telescope for the beginning of the universe. Learning shows us the "redshift of biology". The cholesterol from which we are made had its origins at the origin of the universe (see David Deamer's book "First Life"). And there are powerful clues for this at a more mundane level. Simply counting the variety of possible relationship trajectories (just as counting the behaviour of individual learners) will reveal statistical structures which form normal distributions. Regression structures reveal differentiated groups - the learners who like maths, and those who like music - these too will be normally distributed. But simply to refocus on more fundamental things - love or hate - will also produce the same structures. It is fractal. 

To see education in terms of positions raises an important question about how to make education better. Do we want more kids to pass more exams? Or do we want better positions/relations between people? I don't think the answer to that question is too hard, although some might say that education is about "knowing stuff". So what is "knowing stuff"? We can see that too either as a material process - knowing stuff is about material consumption and production. Or we can see "knowing stuff" as being about energy - the capacity to engage with and position well a large set of relations in harmony with (and not against) our biological origins. I think this is the same as being "in dialogue" with one another.


Wednesday, 31 August 2022

Tacit Revolution

As technology advances in society, there is no escaping the increasing specialisation of knowledge. This may seem like a challenge to those like me who believe that the way forwards is greater interdisciplinarity, or a metacurriculum (as I wrote here: https://link.springer.com/article/10.1007/s42438-022-00324-1). While greater specialisation indicates increasing fracturing of the curriculum and the growth and support of niche areas, more fundamentally it represents the organisational challenge to find the best way to support specialised skills from the generalised organisational frameworks of curriculum, assessment, certification, etc. At the root of this challenge is the fact that generalised organisational frameworks - from KPIs to curriculum - all depend on the codification of knowledge. Meanwhile, hyperspecialisation is largely dependent on tacit knowledge which is shared among small groups of professionals in innovative niche industries, startups, and departments of corporations. 

Since Michael Polanyi's seminal work on tacit knowledge in the 1950s in Manchester University, the educational challenge of transmitting the uncodifiable have been grappled with in industry. The Nonaka-Takeuchi model of knowledge dynamics within organisations has been highly influential in understanding the ways that professional knowledge develops in workplace settings (see https://en.wikipedia.org/wiki/SECI_model_of_knowledge_dimensions). It is in these kinds of dynamics that we are seeing technology drive (and perhaps even accelerate) processes of tacit knowing and externalisation. It's now not only highly technical people whose tacit knowledge must be communicated to senior management, but the technics of machine learning (for example) which are so different from the technics of database design or full-stack implementation, or component manufacture, where each of these technical aspects are interdependent. The communication between technical groups is critical - industries survive or fail on the quality of their internal communications. 

What is critical to making the communications work is dialogue. This may be partly why so many successful technical industries adopt flat management structures and dynamic and adaptive ways of configuring their organisation. That is driven by the dynamics of dialogue itself - the need for technical conversations to flow and develop. Compare this to the rigid hierarchical structures of every educational institution, burdened with its bureaucratic codified curricula. It is completely different. One wonders how it will survive the changes in the world. 

Over the last year and a half, I have been involved in a research project in the University Copenhagen on the digitalisation of education. This project was set up because Universities at least recognise the problem - they are getting left behind in a world which is changing too fast. But like all institutions, Copenhagen believed that the way to address this was to tweak its structures and what it "delivered" - basically to change the curriculum. This was not going to work, and our project has shown it. But this is not because of a failure to get the "right" tweaks to the curriculum. It is because technical knowledge is largely tacit and uncodifiable, and the organisational structures of education cannot deal with tacit knowledge. Indeed, with the bureaucratisation of education, it is even less able to deal with tacit knowledge than it was in Polanyi's time. 

I am now working for the Occupational Health department in the University of Manchester. This is a domain for professionals in health and industry to identify and analyse the relationship between environmental circumstances (work places, etc) and personal and public health. There is so much knowledge in professionals working in this area which is the product of years of experience in the field. Much of it is uncodifiable. 

Uncodifiable does not mean untransmissible. Uncodifiable knowledge can be taught dialogically, and more importantly, technology can greatly assist in producing new kinds of dynamic dialogical situations where this transmission can take place. I am currently looking at ways of doing this in occupational health, but as I do so, I am thinking about what it means for technical education, hyperspecialisation and tacit learning. 

This is almost certainly going to be the trajectory of educational technology. It doesn't look like it at the moment because "edtech" sees itself (tacitly!) as "educational management tech" - we don't really have "technology for learning" as such. It's managers who write the cheques for edtech. But that will change. We're going to need "technology for learning".

There's then another challenge for institutions. Because when we do have "technology for learning", the dialogical situations of tacit learning will not need to be bound by classroom, curriculum, assessment, etc. They can be situated in the world alongside the real activities that people engage in. My own experience of co-establishing a medical startup around an AI solution to diabetic retinopathy diagnosis is indicating this, and there are many other similar startups. Mine started with an educational desire to teach people how to diagnose. It ended with a new product that embraced the educational aspect but did something powerful in the actual domain of work too. 

This is where things are going. I'm not sure this "tacit revolution" is going to be quiet though...

Monday, 29 August 2022

Anticipation and Learning as Information

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. 


Sunday, 28 August 2022

Visualising Learning Statistically

To talk of learning as a process which we can observe is very difficult. When we teach teachers, we teach "theories" of learning which are just-so stories with little hard evidence to back them up barring a few (now famous) psychological experiments. The resort to teaching theory is partly because this is so hard that we would struggle to decide what we should talk about if we didn't just talk about theory. The irony is that talking about theory can be very boring, encouraging professors who didn't think of any theory themselves to talk endlessly about what's written in textbooks - not exactly an example of good teaching! Ultimately we end up with what is easiest to deliver, rather than what needs to be talked about. 

I think the birth of cybernetics in the 1940s was the best chance we had of remedying this situation, but for various reasons, a lot of this transdisciplinary insight was lost in the 1950s and 60s, as other disciplines (notably psychology) appropriated bits of it but lost sight of its key insights. Now, the growth of machine learning is providing a new impetus to revisit cybernetic thinking, with people like James Bridle leading the way in a revised presentation of these ideas (see his "Ways of Being"). One of the most impressive things about Bridle's book is the fact that he reconnects cybernetics to biology and consciousness. That connection was at the heart of the original thinking in the discipline. The biology/consciousness thing is really important - but isn't it just another just-so story? If we don't have any way of measuring anything, then I'm afraid it is. 

Here perhaps we need to look a bit deeper at the whole issue of "measurement" as it is practiced in the social sciences. Another historical development from the 1950s was the increasing dominance of statistical techniques in disciplines like economics. Tony Lawson argues that this was directly connected to the McCarthy period, where anything statistical was "trusted" as scientific and anything "critical" was communist! - as Lawson points out in his "Economics and Reality", the greatest economists of the 20th century (including Hayek and Keynes) were highly skeptical of the use of mathematics in economics. 

Statistical techniques are regularly used in academic papers in education to defend some independent variable's impact on learning. These are usually the result of academic training in statistics for researchers - not the result of a critical and scientific inquiry into the the applicability of techniques of probability to education. But there are fundamental questions to ask about statistical procedures. These include:

  • Why do natural phenomena reveal normal (Gaussian) distributions in the first place? 
  • What is an independent variable, and why should an independent variable (if such a thing exists) produce a new normal distribution?
  • All statistics is about counting - but what is counted in something like learning, and how are the distinctions made between different elements that are counted? 
  • What happens to the uncertainty about distinction-making in what is counted (Keynes made this point in his "Treatise on Probability" with regard to his discussion about Hume's distinguishing between eggs)
  • Where is the observer in the counting process? Are they an independent variable?
  • It is well-recognised that "exogenous variables" are highly significant causal factors - particularly in economics (which is often why economic predictions are wrong). Yet normal distributions arise even when exogenous variables are bracketed-out. Why?
  • While one big problem with statistical techniques is the fact that averages are not specifics, averages nevertheless can sometimes prove useful in making effective interventions. Why? 
  • Why does statistical regression (sometimes) work? (particularly as we see in machine learning)
  • Is a confidence interval uncertainty?
These are the kind of "stupid questions" which never get asked in education research, or anywhere else outside philosophy for that matter. I want here to think about the first one because I think it underpins all the others. 

Normal distributions (calculated using mathematical equations developed by de Moivre, Euler and Gauss in the 18/19th centuries) require a statistical mean and standard deviation to produce a model of likelihood of a set of results.  Behind the reliability of these assumptions is the fact that there is - among the phenomena which are measured - some common point of origin from which the variety of possible results can be obtained. Thus the top of a bell curve indicates the result which is maximally probable having passed through all the possible variations that stem from a common point of origin. 

Mathematically, we can produce a normal distribution from techniques arising from Central Limit Theorem (CLT), where a normal distribution will arise from the sums of normalised random data (see https://en.wikipedia.org/wiki/Central_limit_theorem) . According to Ramsey (https://en.wikipedia.org/wiki/Ramsey%27s_theorem) and others, true randomness is impossible. So the normal distribution is really a reflection of deeper order arising from a single point of origin. What is this point of origin? What does a normal distribution in educational research really point to?

It must lie in biology, and (importantly) the fact that biology itself must have a common point of origin. Because we tend to think of education as a cultural phenomenon, not a natural one, this point is missed. But we are all made of the same physiological stuff. And the components of our physiology have a shared evolutionary history, and it is highly likely that this shared evolutionary history has a point source. So looking at your educational bell curve is really looking at the "red-shift" of biological origins. This is an important reason why it "works".

However, this doesn't explain learning itself - it just helps to explain the diversity of features (behaviour) in a population which can be observed statistically. Much more interesting, however, is to look at how the process of making distinctions arises given that normal distributions are everywhere.

This is why psychophysics is so interesting. The psychophysicists were interested in the distributed differences that different stimuli make on a population. Some differences make big differences in perception: for example, hot and cold. Other differences are harder to distinguish - for example, the difference between Titian and Tintoretto. These differences can also be represented statistically. For example, the orange curve below might be "hot", and the blue curve might be "cold". There is little uncertainty between these distinctions, and within any population, there is no question that what is hot is identified as hot (with a little variation of degree).



But here (below), there is much more uncertainty in distinction making. 

It is this kind of uncertainty in making distinctions between things which characterises learning processes at their outset. Whether it is being able to distinguish the pronunciation of words in a foreign language, or being able to manipulate a new piece of software, among the various categories of distinctions to be made, there is a huge overlap which leaves learners initially confused. 

As the learning process continues, this distinction-making becomes more defined:
So given phenomenon x, the likelihood of correct categorisation of that phenomena is improved. 

But it is important to remember what these graphs are really telling us - that the Gaussian distribution implies a common point of origin. The second graph is the result of a conditioning process upon natural origins - rather like a cultivated garden. But perhaps more importantly, this is dynamic, where the point of origin is ever-present, and exerts an influence on distinction-making. This may be why, despite increases in the ability to make distinctions in one domain, there is a biological requirement to relax distinction making in other domains, and these domains may be related.

"Oceanic" experiences - those that Freud associated with the "primary process" of the subconscious remain an important part of the overall dynamic of distinction-making. This looks something like this:

We make the mistake of seeing learning in terms of moving towards graphs 1 and 3, without seeing the dynamic pulse which relates graphs 1 and 3 to graphs 2 and 4. But this process is critical - without the oceanic connection to distinctionlessness, the coordination mechanism (i.e. reference to origins) which facilitates higher-order distinctions (graph 3) cannot coordinate itself and is more likely to collapse in a kind of schizophrenia (this is what Freud talked about in terms of the superego taking over and the psychodynamics breaking down). 

Looking at learning like this does two things. It invites us to think about our methods of scientific measurement differently - particularly statistics - as a means of looking at life processes as processes which refer to a common origin. Secondly, it gives us a compass for assessing the interventions we make. Our current lack of a compass in education and society is quite obvious. 







Saturday, 30 July 2022

Scientific Economy and Artistic Technique

I wrote (10 years ago!) about my struggle to compose: https://dailyimprovisation.blogspot.com/2012/04/music-meaning-and-compositional-process.html). What's changed in me since?

Now I would say the key word is at point 5:  "If I have enough energy, I will battle on to try and get something down in these gaps, although at some point I get tired and give up" It's that reference to "energy" which has changed for me. What is that? This has become of great interest to me (see this more recent post: http://dailyimprovisation.blogspot.com/2021/09/energy-collages-in-vladivostok.html). How do artists maintain the energy to continue?

This has always been a mystery to me - but it is the essence of what compositional technique is meant to do. Most composers work from a germinal idea which generates possibilities. These germinal ideas are highly economical and concentrated forms of energy. Most commonly, in universities and music colleges, students are told that such germinal ideas relate to patterns of pitches. I have to say I always struggled to relate to this. Pitches seem so abstract as entities - they are just frequencies after all. Music isn't made of pitches, it is made of feelings and energy, and the connection between the abstract patterns of pitches and the feelings always seemed too remote for me. 

In science, a germinal idea which is generative of possibilities is called a theory. Theories are used as a guide in the manipulation of nature and the prediction of events. In an important way, this is also a process of concentrating energy flows. Scientific curiosity depends on energy, and theories concentrate and focus the labour of scientific inquiry to produce new knowledge. There is almost certainly a physiological driver for theory production in science.  

Many successful modern composers do not have the hang-ups I experience about the abstractions of notes. Rather like mathematicians, they seem to delight in the manipulation of abstractions as a source of their composing work. What I believe they possess when they do this is a highly compressed representation of the energy of the work which is comparable to the scientist's theory. They use the abstractions to unfold the energy over the long period of time that it takes to get the actual notes down on paper. That is how they are able to get the whole thing done.

Having said this, there is a problem in becoming too fascinated by the mathematical manipulation of pattern to produce sound. It is like a scientist becoming too fascinated by their concepts. While such procedures can unfold music of energy and beauty, sometimes (perhaps quite often) it sounds abstract and remote. Techniques like serialism were developed to free the conscious mind of cliché so as to facilitate the authentic connection between the subconscious creative mind and its conscious expression. It was intended as an "unlocking" procedure. But an obsession with mathematical procedure and pattern carries its own clichés. Brilliance in science also effects a kind of psychodynamic unlocking. 

Over the last couple of years, I've become interested not in notes but in physiology. When I improvise I find that the concentrated and economical forms of energy are not in any pattern of notes, but in the pattern of my fingers. So often my improvisation exploits the economy of my usage of my hands. I've recently started to notate this physiological concentration. The advantage this has is that unlike abstract patterns of notes, the concentrated pattern of physiology does contain feeling and energy. While I can notate the physiology, I can also feel it physically, and in feeling it physically, the energy of its unfolding (so I can get notes down over time) can also be controlled. 

I wonder whether the way artists manage the energy of creation is a determiner of artistic style. Every period in history brings environmental stresses which impinge on the ability to manage the flow of energy in artistic expression. Ours is a time of "entropy pumps" - we live in an age of constant distraction. That may mean that our management of creative energy may have to be situated more closely to our bodies. Overly cerebral approaches may lead to a disconnect between what is said and what needs to be said (although maybe I'm being too cerebral!). It may be ok for writing blogs and academic papers - but really, that is a waste of time and energy. 

The ability to concentrate energy in a germinal form - which may be common to both art and science - is really the ability to facilitate the steering of the creative (or empirical) process. Something that facilitates steering in systems terms is a trim-tab. The creative process - and certainly the process of improvising - is rather like a bird in flight. The very best scientific work also has this quality of free thought. Technique is not there to direct the course of creativity. It is there to loosen the constraints which would otherwise prevent the freedom of movement of creative processes in turbulent times. 

Tuesday, 26 July 2022

Prufrock's Soul

A university friend said to me the other day that she felt writing academic papers was not nourishing in the same way as more artistic things that she did (but did less since she spent more time writing papers). I agree, and this makes me want to know more about differences between the qualia of different creative activities. What is nourished when the soul is nourished? What might be the mechanism?

Spiritual nourishment is visceral. There is a sensation, perhaps somewhere near the solar plexus, which is activated with certain activities which might be considered to be nourishing. Personally, my solar plexus rarely responds when I am writing. I know this because as I write this, I cannot feel it: the activity is in my head, not my belly. When I think more about the specific feeling of "soul nourishment" then I will rehearse those things which produce it - gazing at a beautiful sunset, beautiful moments in music, water - both still and a flowing stream, a cathedral or grand library.

There is something primeval about these experiences: something timeless. In the evolutionary theory of John Torday, as biological entities, we are phenotypes seeking information to return us to an original evolutionary state. Sometimes the seeking can go wrong and we simply end up lost. When T.S. Eliot writes in the "Love Song of J. Alfred Prufrock": 

"I should have been a pair of ragged claws

Scuttling across the floors of silent seas."

The ragged claws are the primal evolutionary state; Prufrock's weary, regretful, sexually repressed, empty-souled persona is the result of evolutionary accretions in search of a return to the simplicity of evolutionary origins which have only further obscured any deeper satisfaction. And Prufrock is lost. But the poem points to a kind of vector that connects primal origins to an empty life in search of meaning.

The point about this is that Eliot's soul was nourished in writing about a lost soul. The similarity to Dante is obvious. But what is it about Eliot's art which enables him to articulate this connection? 

Great poets, artists and composers harness energy. John Galsworthy commented about art and energy that: 

Art is that imaginative expression of human energy, which, through technical concretion of feeling and perception, tends to reconcile the individual with the universal, by exciting in him impersonal emotion. And the greatest Art is that which excites the greatest impersonal emotion in an hypothecated perfect human being.

(I'm grateful to Marie Ryberg for drawing my attention to Dewey's "Art as Experience" where he quotes this Galsworthy passage.) 

Eliot's poem does this. And the writing of academic papers does not have this effect. The question, it seems, is about energy. He understood the energy vector that connects his art and technique to a deeper truth about the universe, and the plight of J. Alfred Prufrock. 

Academic writing is rather deathly by comparison. The desire to explain away things which can't be explained, and conform to expectations of "proper referencing", "cogent arguments", "rigorous methods", etc, kills the soul. It might reward academics with promotion within an insane (and increasingly broken) system, but unless the work is truly ground-breaking, it amounts to little more than paraphrases of what has gone before. This is particularly true of education research.

When we do more deeply creative things, however, we engage with the energy that connects the scuttling claws with our present state. The regression connects us to where we come from, and where we are going. The are a number of hormonal and epigenetic factors which kick-in in the process. Moreover, the technique of creative work is very similar to what Galsworthy describes: a technical concretion of feeling and perception. The artist's challenge is to develop a technique whereby this can be managed. 

The deep challenge with this is that, of course, education does not see itself in relation to primal origins and energy vectors! It sees itself in relation to the development of independent "selves" as economic units in the making. But primal origins are what connect us to each other. What we imagine as our independent "self" is merely an apparatus for collecting epigenetic information and eventually transferring it to a new zygote, which will grow to some new apparatus for collecting information. 

Darwinian natural selection privileges the organism surviving in its environment, whereas the organism may merely be a vehicle for passing epigenetic information back to a zygote. It's ironic that Darwin's model probably had its origins in Darwin's schooling, while the establishment of the evolutionary model has reinforced an attitude to educational growth and development which has pushed creativity out in favour of STEM-related nonsense. 

Saturday, 16 July 2022

Disentangling Entanglement in the Social Sciences

One of the most unfortunate aspects of increasing interest in topics like complexity and systems is the appropriation of scientific terminology to obfuscate the kinds of problems which the systems sciences were developed to enlighten. It's not exactly the same problem as Sokal (Fashionable Nonsense - Wikipedia) identified 20 years ago as a kind of intellectual scientific posturing - that, he argued, was at worst a kind of fraud, and at best, intellectual laziness. What we see now is more of the latter, but it exists in a dominant normativity where it's almost impossible to suggest that simply saying stuff is "complex" is to do no more than posit a blanket "explanatory principle" which explains away intellectual difficulties, rather than invites the question "how? so then what?".  

Entanglement - as it has been used by Latour and others - is a case in point. Latour has positioned himself carefully here (see Bruno Latour, the Post-Truth Philosopher, Mounts a Defense of Science - The New York Times (nytimes.com) because he is aware of the problem (and as someone who began their career doing information theoretical analyses, he should know), but that hasn't stopped a sociomaterial industry (particularly in management science and education) growing up with long words and nothing much to say. Like all industries, it seeks to defend its position, which makes challenging it very difficult, and any practical educational progress even less likely. 

In physics, entanglement refers to the specific state of affairs in quantum mechanics where non-local phenomena are causally connected in ways which cannot be explained by conventional (Newtonian, locality-based) physics. If there is a fundamental underpinning idea here, it is not so much the weird interconnections between what might be seen to be "separate" variables, but rather the distinction between local and non-local phenomena, and the ways in which the totality of the universe is conceived in relation to specific locally observable events. Talking about entanglement without at least considering it in the light of totality and non-locality is like talking about the reality of ghosts on a fairground ghost train. 

Part of the problem is that we have no educational cosmology - no understanding of totality, or rather how education fits in a totality of the universe. This seems a grand and ambitious task - but if we deny that such a thing is possible, we then cannot defend allusions to science to help us address educational problems. This is why better educational thinkers are thinking about physics, education, technology and society together (this is good: Against democracy:  for dialogue - Rupert Wegerif). James Bridle's new book "Ways of Being" is also better - containing a lot of good stuff about biology and cybernetics -  although again, it's hard to see a coherent cosmology... (very interesting interview between him and Brian Eno here: Brian Eno and James Bridle on Ways of Being | 5x15 - YouTube)... so there's lots to do. 

We need not only to ask ourselves better questions, but think of better methods for addressing those questions. Some things don't need to be that complicated, and the seeds for new thinking are often in the past. Warren McCulloch's early work on neural networks (A heterarchy of values determined by the topology of nervous nets | SpringerLink), for example, contains these fascinating diagrams:

The above diagram explains McCulloch's notation: the continuous lines at the top are the nervous system, while the broken lines at the bottom are the environmental system. Receptors receive (transduce) signals from the environment, and effectors cause changes to the environment through behaviour of the organism (that's transduction too). There are two lines above representing (for example) two variables or categories of perception (perhaps "black" and "white"). But this diagram above does nothing: what goes in comes out.

The diagram below is much more interesting. The feedback of each category is wired into every other category (rather like the Ashby homeostat), and this keeps the thing in flux. What does that mean for our values? Perhaps left to our own devices we would forever be shifting from one category to another. But in communication with other such systems, stabilities in the perceptual apparatus of many people will result in values which can be codified and assumed to be "fixed" (although what appears static is an epiphenomenon of a continuous process):

Are such values and perceptions "entangled"? In the sense that Latour and Orlikowsi discuss it, yes. And indeed, the sociomaterial dogma becomes much clearer as a cybernetic mechanism conceived 80 years ago. It simply requires rediscovering how perception was thought about at the beginning of cybernetics. Intellectual amnesia is the root of our current problems with complexity.

Having said this, McCulloch didn't address totality in a satisfactory way. He knew the challenge. In his paper on "What is a number" (see Warren S. McCulloch: What Is a Number, that a Man May Know It, and a Man, that He May Know a Number? (vordenker.de)) he says:
"The inquiry into the physiological substrate of knowledge is here until it is solved thoroughly, that is, until we have a satisfactory explanation of how we know what we know, stated in terms of the physics and chemistry, the anatomy and physiology, of the biological system"
That is an appeal to grappling with the science of totality. We are going to need to take educational research a lot more seriously, and have a very different kind of research effort, if we are going to get close to this. Its importance, however, is urgent. The study of education is not a study of a particular kind of social practice. It is the study of how organisms which live for a short period of time, organise themselves to ensure that future generations can survive. 


Tuesday, 5 July 2022

Cells and Sociomateriality

The sociomaterial gaze looks upon the world as a set of interconnections. Running through the "wires" of this web is the agency of individual entities - humans (obviously) and (more controversially) objects and technologies constituting organisational structures, power relations, roles, etc. To deal with the complexity of this presentation of the world, sociomaterialists evoke ideas from quantum mechanics like "entanglement" and (occasionally) "superposition" to explain the complex interactions between the components, looking to science (as represented, for example, by the interpretation of Bohr by Karen Barad) to supply sufficient doubt over the ability to be more precise about what is actually going on. If I was being unkind, I would say the end result has been a lot of academic papers with long words which mystify more than they enlighten. Even critiquing it seems to invoke complex vocabulary: "heterogeneous dimensions are homogenized in a pan-semiosis" (Hagendijk, 1996 - see https://www.leydesdorff.net/mjohnson.htm) - well, yes. 

Gazing at the world's complexity and trying to explain it by purely focusing of manifest phenomena is like trying to explain the universe but ignoring its expansion. The synchronic (structural) dimension alone will not suffice. History - the diachronic dimension - is critical to get a perspective which is more scientifically defensible. It is a profound change in perspective: the diachronic dimension enables us to see the world in 3D. This means that we have to draw away from looking at the relation between objects/technologies and people (for example), and instead focus on life itself  - to understand not only life's characteristics, but the mechanisms behind its creation of the material environment with which sociomateriality is so fascinated. This is a project connecting Lamarck, Bateson, Schrodinger and Bohm with recent work ranging from astrobiology, cellular evolution and epigenetics. 

I want to explain why this diachronic perspective is a much more powerful way of looking at education, technology and human life.   

Every one of my cells has a history. Not just the history of where it began in me - which was in one of the three "germ layers" of the zygote that eventually grew into baby me - but a deeper history of how each of the (roughly) 200 different cells types emerging from the zygote acquired their individual structures and properties. Each of them has a history much older than me. Each of them acquired different components (organelles) which we now see as a process of absorption of externally existing components in the environment: endosymbiosis. Cellular endosymbiosis occurred in response to environmental stress. Early cells had to reorganise their structures and functions in order to maintain: 

  • homeostasis within the cell boundary
  • balance with the external environment
  • energy acquisition from the environment 
Through endosymbiosis, each of my cells carries a historical record of its own evolution. For example, the movement of animals from water to land is carried in the development of lung cells, which evolved from the cells of the swim bladders of fish. Since we are all made of the same cells, this historical record within our constitution unites not only common members of a species (all of us), but all cellular life.

To what extent might we "know" this? To what extent does our physiological knowledge play out when we sit at our computers or stare at our phones? Moreover, if we do intuitively sense our deep interconnections with nature, by what mechanism of nature do we behave as if we deny this completely?

This is to turn the fundamental questions of ecology (and particularly, cybernetic ecology - Bateson, etc) upside down. It is not to ask how we are connected, but how human relations have evolved to be disconnected. Is there a logic here? Our scientific problem is that if we look for the logic of human behaviour taking the unit of analysis as human relations (or worse, the individual), we will come to the conclusion that only specific kinds of relation "go wrong". Some relations may appear to "go wrong" more than others, but in a deep sense, we all suffer from bad relations. 

This question of the "evolution of disconnection" cannot be addressed unless we consider the cellular origins of life which connect us all, together with the ways in which the evolutionary history of cells is programmed into us. Human disconnection may be the activation of older mechanisms in cellular development which, at the scale of cells or small organisms, may not have been as devastating as we now make them. 

Our social engagement in the context of a technological environment is not "entangled" (whatever that means), it is an "evolved disconnection" from nature. We communicate - make common - our sense of being human - of having this collection of cells, which we understand to be common. That is how the empathy, love, and the expression of doubt work. In the context of that communication, we also communicate our physiological reaction to the material artefacts around us, which are in turn the results of historical communications. In that historical communication, there are the seeds of our current evolved disconnection which may be sometimes be felt as alienation or frustration, and (sometimes) as energy, excitement and flow. At the root of that evolved disconnection are deeper natural processes of cellular evolution. The better we can understand those, the better equipped we will be to steer our way through our current (and dangerous) state of evolved disconnection. 

This is not to invite further metaphysical speculations. It is to invite something more practical. Our disconnection from nature is now throwing up tremendous turbulence in our existence. Like a plane flying through turbulence, the challenge is steering, and the tapping in to the deep knowledge to do that steering well. I have been wondering recently if cellular evolutionary history is the hidden mechanism of biological steering - a kind of "trimtab" as Buckminster Fuller described. If that is the case, if we can grasp it, we can reconnect our steering with the natural world. Might we have technologies to help us?

Sunday, 26 June 2022

Learning, Dialogue and AI: Offline initiatives and Political Freedom

I'm running a small EU project in July called C-Camp. The idea is to instil and explore computational practices among students from 4 European Universities (Prague, Copenhagen, Milan and Heidelberg). I wanted to create something for it which built on my experiences in Russia with the Global Scientific Dialogue course (Improvisation Blog: Transforming Education with Science and Creativity (dailyimprovisation.blogspot.com) - about which a paper is shortly to appear in Postdigital Science and Education). 

In Russia, the vision was to present students with a technological "cabinet of curiosities" - a way of engaging them in asking "this is interesting - what do you make of it?". It was the uncertainty of encounter with technological things which was important - that was the driver for dialogue, which dominated the course. C-Camp is very much in the same spirit. 

This time, I have been a bit more ambitious in making my cabinet of curiosities. I've made a cross-platform desktop app using ElectronJS which incorporates a tabbed web-browser, alongside self-contained tools which make available learner's data to the learners (and only to the learners). The advantage of a desktop tool is that, apart from the learners being able to change it (my programming and design is merely functional!), nothing personal goes online, apart from the traffic in each website.  The data of engagement with the tools - which is something that is usually hidden from learners - then becomes inspectable by them. There  are lots of "cool tools" that we suggest exploring (like the amazing EbSynth below)

The pedagogy of the course will then be to explore the data that learners themselves create as they process their own uncertainty. It's messy data - which can be an advantage educationally - but it illustrates a number of important principles about what is going on online, and what data big tech companies are harvesting, and how they are doing it. 

More to the point, by having a desktop tool, there is an important thing to say that "edTech doesn't have to be like the LMS!". Not everything needs to be online. Not everything needs to be harvested by corporations. And more to the point, if individuals were more in contact with their own data - particularly their own learning data - there are opportunities for deepening both our learning and our engagement with technology. So supporting students in downloading and analysing their own Facebook data can be part of a journey into demystifying technology and inspiring the imagination to look "beyond the screen"

 


One of the things I've done is to integrate 2 AI services. One of them uses the OpenAI service, which is online. The code for doing this is quite simple, but the important thing is that the processing happens remotely on OpenAI's servers. 

However, the other AI service is local. I've integrated the VGG16 model with Imagenet data so that students can upload and explore image recognition. The model and the code are all on the local machine. The point to make is that there is no reason why OpenAI shouldn't work like this too - other than commercial reasons.

What fascinates me about this is that for all the anxious talk about AI and its supposed "sentience", nobody talks about the technical architecture which basically up-ends the idea that everything has to be online. Large-scale language models are basically self-contained anticipatory dialogical engines which could function in isolated circumstances.

Think about this: imagine in a non-free country like Russia or China, where the authorities seek to monitor and control the conversations that individuals have, suddenly individuals can have conversations which are not monitored - simply by being in possession of a particular AI file. 

I'm doing a demo of OpenAI tomorrow in China. The last time I did it there, it worked. I doubt it will work for much longer. But it's easy to envisage a future where a market for specialised language model AIs start to infiltrate the underworld allowing people to have "prohibited conversations". That could mean both very good things for social organisation and freedom from oppression, and bad things in terms in terms of crime. 

That is one of the more fascinating things to discuss in C-Camp. I think I might be more careful with my Chinese audience!




Saturday, 25 June 2022

How Learning Feels

When learning works, it feels like a burst of energy. It is the energy of an explosion of new possibilities brought about through some revelation. It is a spiritual moment (something we hardly ever acknowledge) - even when it is learning about unspiritual things. Like the discovery of a new physical energy source, we can live off the energy of new learning for some time. 

Striving for this moment is not easy. Yet we are driven towards it for reasons we do not understand. Teachers often assume that the motivation is produced by the mere operation of the education system. But the education system exists because curiosity and the motivation to learn exists. The system has no explanation for curiosity, and it struggles to conceive of ways of learning outside of itself.

New possibilities are possibilities for new social action. It is not just what some sociologists call "agency", but a transformed social configuration. A learnt skill is a transformation in social connections and conversations. It is new dialogical potential. And dialogical potential begets new possibilities for learning and energy distribution among others. To talk of the energy of learning, we should also talk of the energy of teaching. There is an energy flow in these dynamics.

In natural ecosystems like ponds and meadows, energy dynamics are very important. Ecosystems maintain themselves by keeping the energy flowing between co-evolved co-habiting system components. If the flow is stopped - by environmental damage, for example - the ecosystem dies. 

Education systems have become tragically good at preventing flows of energy. Instead of allowing energy to flow, education systems hoard it, exploit it, seek individual gain from it, use it to make money, and seek to make ourselves "powerful" as if we are independent from everyone else. 

We do this partly because we do not understand the dynamics of energy. If we did, we would take music much more seriously because it is one of the few human activities which exhibits energy flow in a pure form in a human system.

Intuitively, I think we know this. It is a symptom of the education system that it prevents us from "knowing" what we know deep down. Somehow we need the education system to adapt so that  it helps us to steer ourselves through what we know deep down. It needs to ease our steering - particularly in uncertain times. It is a transformation from hoarding knowledge to assisting steering. Then perhaps the steering of learning will feel more natural.


Wednesday, 8 June 2022

Trimtabs and Loosening Creativity

Creative processes are often difficult. It is hard to steer through distractions, uncertainty, self-doubt, dead-ends, etc. The steering becomes "heavy". So what's wrong with the mechanism, and what might be done to loosen things up to make the process more navigable?

The construction of niches for creative work is critical. It is the niche within which new things can grow. From a technical/theoretical perspective, niches are the result of redundancy. In his description of the Zone of Proximal development, Vygotsky said as much (without using the word "redundancy"), in highlighting the importance of imitation in what he called the "learning" process, and arguing that "development" lags behind "learning". In the same way, creation lags behind redundancy - it doesn't matter what kind of creation it is - it can be technical, artistic, organisational, theoretical or scientific. 

Margaret Boden talked once of the creative work of Spanish seamstresses making Flamenco dresses. She said "they do one layer, then another, then another, then another... what's going on there?" It's the same with things like mosaic, quilt-making or knitting. I didn't know enough about redundancy at the time to suggest it as an explanation, but I think she was already thinking this. This is niche construction. 

It is something we tend to ignore in education because we have become so obsessed with outcomes and products, seeing the processes which produce them as "problem solving". The word  "solving" is interesting because it really means "loosening" - solvere. That's not how people who talk about problem solving think about it. But if loosening really happens, then it makes the "steering" easier.  

Buckminster Fuller's idea of a trimtab is a loosening device. It literally loosens the steering, and it does it by creating a niche for steering - simply by  adjusting the pressure on a rudder or a wing. This tiny thing at the back-end of the navigation process is the thing that makes everything else work. Now perhaps its not stretching things too far to say that trimtabs create redundancy. Without them, there are a variety of different forces and pressures operating on the wing - so much variety that there is no single steering movement that can manage this variety. The trimtab reduces the variety by increasing the constraint. It's rather like a spider spinning a web. By creating a uniform area of lower pressure,  steering can be assisted. 

The trimtabs of our organisations lie in the redundancy of communication among their workers. Where there is high redundancy, we will also see what we might call "collegiality". Collegiality, team working, and a shared mission can all create the niche for organisational creativity. An absence of it will make creativity very difficult. 

Our organisations do not have operational trimtabs. The only lever they can pull is the departmental meeting - and this has become a ritual which often serves very little purpose. There is a deep need for exploring new mechanisms for institutional organisation. The answer to this lies in technology - but not the kind of surveillance technology which is often talked about (like "learning analytics"). Surveillance will not produce collegiality. Quite the opposite. 

We need to use technology to provoke dialogue among colleagues. It is through the dialogical engagement among colleagues that effective niches can be established. This is not to see technology as instrumental, but dialogical. AI may be our best opportunity to do something like this, and if there is one single challenge that faces us with that technology, it is that we misuse it to tighten, and not loosen, the steering.   

Saturday, 4 June 2022

The Cybernetics of the Trimtab Society

Over the last seven years, I've been heavily involved in a medical diagnostic project which unites human and machine judgement. This has always been cybernetic in my mind (and it was cybernetic insights which led to some pretty cool machine learning that sits behind it). It's about to be commercialised which is very exciting, not least because the technology is applicable to fields far beyond medical diagnostics - education, management, organisational risk and public health are all within scope of potential application. 

Cybernetics relies on simple rules and metaphors, but these work in a wide range of contexts. The Law of Requisite Variety is the most important - the amount of variety (or complexity) that a controller has is the limit of the complexity of any system that it can control. Most simply, variety eats variety. Since most systems have to survive in environments of greater complexity than they possess, they must establish a controlled relationship with their environment through attenuation (selecting what information to pay attention to and what to ignore) and amplification (use their capabilities and understanding to create a niche in the environment - for example, a spider spinning a web). This can balance the variety equation.

A simple mechanical metaphor of cybernetics is the Watt Governor on a steam engine. The engine's speed, represented by the spinning of its flywheel, is controlled by a device (the governor) which uses centripetal force generated by the speed of the wheel to either slow down or speed up the flow of steam to the engine. This works because the wheel has exactly the same amount of variety as the governor: whatever state the engine is in is matched by a corresponding state of the governor.

This is fine as a metaphor, but in social life, there is no one-to-one mapping of environmental complexity to controllers, so we end up with very complex patterns of attenuation and amplification which can create dangerous positive feedback to the system. We are living through this in many ways at the moment - not just in the climate crisis, but in the political feedback from our online communication, the economic system producing runaway inequality, the Ukraine war, and so on.

Buckminster Fuller drew attention to a different kind of cybernetic feedback mechanism - the trimtab. Trimtabs are the small edges on the back of wings which wiggle as the plane is flying, and which serve to make the pilot's job of steering and stabilising the plane easier. In other words, the trimtab is part of a mechanism which connects the pilot to the machine. It is not self-enclosed like the Watt Governor, but translates the environmental conditions into a potentially controllable situation, which would otherwise be very difficult to control. 

Buckminster Fuller thought so much of trimtabs that he had "Call me trimtab" written on his grave. He argued that the most important part of steering was not at the front, but at the back, and that each of us could be part of a "social trimtab" each feeding information about environmental conditions in a way which could facilitate effective steering. 

The diagnostic AI which I and our team have created basically works like this. With our work, the "pilot" is the doctor, but the pilot's job is to steer through different environmental conditions in terms of differing degrees of prevalence, diagnostic certainty, organisational complexity, health economics, risk and potential positive feedback. To achieve this has entailed a very different approach to AI. Conventional AI is simply used to provide "answers", often with the intention of replacing the "pilot". That's not a good idea because it throws away huge amounts of information which can be critical to understanding the nature of the challenges we face. The trimtab (and our trimtab AI) by contrast preserves information, transforming complex data into the conditions wherein effective decisions can be made. 

I've always felt that the most important thing education should do is to harness the uncertainty of individuals, because this information is information about the nature of our environment. What I've never been entirely clear about is how this "harnessing" looks - lots of forums, debate, etc, don't seem to work and in fact amplify social complexity. So we need a way of organising the many different signals coming from society as a means of facilitating effective steering for the planet (or Spaceship Earth as Fuller said). This may be the most powerful and effective use of AI. 

Friday, 13 May 2022

Dialogical Design

Thinking about thinking may be essential to dialogue. This isn't because dialogue is solipsistic - although an internal conversation might well be. It is more because dialogue involves the creation of uncertainty: either uncertainty within oneself or the social uncertainty which new utterances reflecting internal uncertainty create in communication. Dialogue is what we do to manage uncertainty, and thinking about thinking is how we generate uncertainty. Since thought and utterance are both processes now mediated by technology, this "thinking about thinking" is increasingly "thinking about technology". 

In his famous essay "The Question Concerning Technology", Heidegger sets out to make this point at the very beginning. Before we get to the rather complicated terminology that Heidegger uses to describe the phenomenon of technology ("enframing", etc), he makes a point relating to "thinking about thinking":

"In what follows we shall be questioning concerning technology. Questioning builds a way. We would be advised, therefore, above all to pay heed to the way, and not to fix our attention on isolated sentences and topics. The way is a way of thinking. All ways of thinking, more or less perceptibly, lead through language in a manner that is extraordinary. We shall be questioning concerning technology, and in so doing we should like to prepare a free relationship to it. The relationship will be free if it opens our human existence to the essence of technology. When we can respond to this essence, we shall be able to experience the technological within its own bounds."

This is Heidegger in dialogue with himself in the context of uncertainty created by technology and existence. Irrespective of what we might think about his eventual conclusions, this is an supreme example of what it is to think. 

If we were to say that thinking about thinking is essential to dialogue, what would we say if there was utterance without thought about thought? Could this be dialogical? If not, why not?

At a recent online event, Rupert Wegerif made the point that fascism is not dialogical, and that those instances of fascist/extreme right-wing posting on Twitter weren't dialogical, while other interactions on Twitter almost certainly are. Is it the recursiveness of thought which distinguishes these things? 

An interesting question arose in this session as to whether TikTok was dialogical. TikTok appears to be the epitome of what Heidegger would call "falling" - the kind of thoughtless action that we engage in where the "readiness-to-hand" of the technology masks the world as it really is: like drone operators staring at computer screens and pressing "fire". We have the same experience in other forms of engagement with technology where we go into "autopilot" (driving is a good example). Is TikTok autopilot? 

My colleague Danielle Hagood objected to the idea that TikTok wasn't dialogical. Part of TikTok's  appeal lies in the counterpoint between the fallenness of the swiping of videos, and an inquiry into the behaviour of the algorithm. I think she's right - this inquiry into the behaviour of the machine, which is also an inquiry into our own thinking and reaction - is dialogical. 

I suspect it is a category mistake to talk about dialogue being facilitated by particular platforms or technological activities - one activity is dialogical and another isn't. That sounds rather like Theodor Adorno's criticism of pop music: that the only music that was worthwhile was that from the 2nd Viennese School. We (I) don't want to become a digital Adorno, sneering at all the fun people have with technology! All digital activities (all activities) provide the stimulus for thought to think about itself: it is this that makes them potentially dialogical. 

This is important when we consider conversation as an activity. Not all conversations are dialogues for exactly the same reason that not all technological activities are dialogues. Rupert's point about fascism is spot-on here. Fascism is fascism because it has no reflexivity on its own thought. To live in a non-dialogical world is to be both prevented from reflecting on our own thought (through fear) and/or to be prevented from uttering inner doubts in public which contributes to the external uncertainty. We see both these conditions in Russia at the moment. Of course, the Russian state proclaims a rationale for what it is doing - but it's manipulation of the media is characterised by the generation of non-questions in the public domain - often concerning the use of nuclear weapons. It admits (and permits) no genuine articulation of uncertainty.

This anti-dialogical condition is designed. So could we design an opposite condition: a condition wherein thought is encouraged to think about itself? 

I think the answer to this question is "yes", but I think there is no way of doing without this entailing a reflection on technology. Thought is inseparable from technology - from the medium, the technique, the technics and the politics. The condition for dialogue is a condition where the uncertainties that must be generated by dialogical processes are generated by unpicking the technological domain as much as the psychological and social domain. 

We need to think of a new kind of technology which can support this: something where the action taken with a tool leads to reflection on the operation of that tool and its relation to thought. This may be where the current drive for digitalization in education takes us. I'd be tempted to call it "Second-order educational technology"