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. 

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"

Learning technology and "Learning technology"

I have been heavily involved in promoting digitalisation at the University of Copenhagen for a year or so. When people ask what this is really about, I have found the simplest answer is to say that it is about encouraging students and teachers to look "beyond the screen". I often demonstrate this by simply pressing "CTRL-SHIFT-I" on my keyboard in a browser to reveal the Javascript console. It's perhaps analogous to producing a microscope in the natural environment. An invitation to ask more questions and explore new possibilities: to ask "What if...?"  

In the same way that we would encourage people towards deeper self-examination as part of their education, so I think it is becoming more important that a (related) technological-critical examination takes place within the digital environment in which we all swim. For the generation of students we are now teaching, the digital environment is a natural environment, whether they are comfortable in it or not - after all, there were always plenty of natives of the non-digital natural environment who were never comfortable in it!

Just as we would encourage people to explore and inquire about the natural environment, it seems reasonable to extend this to an inquiry into this "new nature", which is really as much an inquiry into ourselves as it is an inquiry into technology. Indeed the central issue of digitalisation is that it concerns the boundary between self and world which education has so-far been able to wash over. 

Faced with the mind-bending questions about identity and environment, sociology and psychology, it is much easier to stay rooted in traditional disciplines - both for students and staff. Moreover, our institutions have constructed themselves around these disciplinary sanctuaries. There are many reasons for an institution both to encourage "digitalisation" and to resist it. The encouragement comes from an a perception of existential threat - if traditional distinctions break down, then the raison d'etre for the institution is threatened, while if institutions fail to help students to adapt to the digital world outside, then they will be seen to be irrelevant. Digitalisation sits in the same camp as many other distinction-blurring issues: sustainability, decolonisation, and gender fluidity. These are all, I suspect, manifestations of deeper processes in our changing biological relation with our environment, our history, our institutions, and each other.  

The institution responds to this not with any fundamental organisational adaptation, but rather by declaring these things as "issues" or "agendas". So digitalisation, along with so many other things, has become an "agenda". Institutionally, "agendas" can be addressed by sticking something new on the curriculum, as if all that is required is a "bit more knowledge". So writing an essay on transgender rights (for example) will somehow address deep-seated and culturally established norms of bias and (often) bigotry. Is compliance with the "digitalisation agenda" merely satisfied with an essay about data privacy in the metaverse? What use is that? It keeps everyone busy, but does little to address what is really happening. 

So what about technology in this "learning"? What about "learning technology" for "learning technology"? Institutions have adopted a particular position with regard to technology for education which is now causing problems in its thinking about adapting to the challenge of the digital environment. Partly this has been caused by the commodification of technology in education, which has actively prevented students looking "behind the screen". Yet if we actually try to engage students in "looking behind the screen" there are some pedagogical challenges which have yet to be solved, but which are critically important. They might be listed:

• How to avoid this becoming "computer science"?
• How to make technical engagement personally meaningful?
• How not to alienate students and teachers?
• How to adapt assessment in ways which encourage technical exploration and creativity?
• How to diversify activities so that students with different skills and dispositions can engage in activities that are right for them?
• How to maintain interest and creativity when technical engagement often involves a quick descent into (often confusing) technical details which are far-removed from intended aims?
• How to connect technical engagement to personal identity and spiritual development?
• How not to throw out the disciplinary baby from the bathwater - transdisciplinarity cannot replace disciplinary expertise 

These are both pedagogical questions, and structural question within the university. They are challenges related to the act of "learning technology". There is, as yet, no sign that universities are willing to consider structural changes - particularly in assessment practices. So digitalisation will continue to sit as another "agenda". They want "learning technology" but cannot find a way of supporting the deeper process of personal inquiry involved in learning technology. 

But how could it be different? Perhaps one way forward is to think of how all the agendas piling onto education are symptomatic of a structural failing of the institution in a fast-changing world. It's like the British royal family now being increasingly confronted with the legacy of slavery - a legacy which biology is demonstrably showing the 200 year old epigenetic inheritance in heightened levels of diabetes, hypertension, stress and depression among black communities (see for example, Post Traumatic Slave Syndrome | Dr. Joy DeGruy (bethehealing.com)). This is how science really challenges existing structures and practices. 

So what do we do? Should we throw away those structures? (Royals perhaps!) But we should invite innovative systemic approaches to restructuring to provide the space for personal exploration in a world which is moving fast away from traditional understanding. Assessment is where I would start - it is the principal constraint that keeps everything else stuck in its ancient shape. 

Digital Shadow

Carl Jung always warned us not to overlook "the shadow" - the archetype of the subconscious from which the conscious mind disassociates itself. Doing so will inevitably mean that at some point the shadow will take over and cause a crisis of far greater proportions than that which might have resulted had it been negotiated with sooner. Recent events and world history suggest that these shadow dynamics are reliable. There is no world which doesn't cast a shadow. This is why Shakespeare remains our most reliable guide to human behaviour. 

Its curious perhaps that our digital technologies exist through light. We may understand well enough that the shadow that is cast by the light of the screen lies within us. But how do we negotiate our shadow in this digital light? The psychoanalytic answer is to talk about it. Perhaps drama and storytelling are ways we can share experiences of the shadow (just as it was in the classical world) - but it can objectify the shadow in the collective imagination in a way where we can become complacent that we have put the shadow in its place. This "collective shadow" can be manipulated - which is something we are seeing very clearly in Russian state propaganda at the moment.  The shadow becomes the "other" rather than part of each of us. We see this "othering" online.  

The problems of fake news in the Trump campaign, Brexit, etc are striking examples of this kind of "othering" of the shadow. When Everett Hughes asked of the Germans during the 2nd world war "How could such dirty work be done among and, in a sense, by the millions of ordinary, civilized German people?", his answer is that if the dynamics of "in- and out-groups" are organised such that one group is "in" and everyone else "out", then the capacity for good people to do dirty work is increased. Hughes argues that in a richly developed society, there are many small social groups, all of which have their "in" and "out" dynamics (see Good People and Dirty Work on JSTOR)

"A society without smaller, rule-making and disciplining powers would be no society at all. There would be nothing but law and police; and this is what the Nazis strove for, at the expense of family, church, professional groups, parties and other such nuclei of spontaneous control. But apparently the only way to do this, for good as well as for evil ends, is to give power into the hands of some fanatical small group which will have a far greater power of self-discipline and a far greater immunity from outside control than the traditional groups. The problem is, then, not of trying to get rid of all the self- disciplining, protecting groups within society, but one of keeping them integrated with one another and as sensitive as can be to a public opinion which transcends them all. It is a matter of checks and balances, of what we might call the social and moral constitution of society"

It is not the beliefs of individuals which blind them to the shadow, but the dynamics of society. Here it is important to reflect on what the internet has done to those dynamics. The disembodied Balkanisation and digital othering which characterises online communities does not constitute the "nuclei of spontaneous control".  As we have seen, instead it renders communities susceptible to fanatical control because each community objectifies its shadow as "other", rather than being able to see it in themselves. If Elon Musk is really serious about improving Twitter, this is what should be understood. Importantly, it is not specifically about "algorithmic control", "AI" or even "confirmation bias". Indeed those critiques are an example of "othering" of technology - which itself contributes to the problem. 

One of the deepest challenges I think we face today is that confronting our shadows cannot be done without understanding of technics. Digitalisation is almost always presented in its light - we do this to "innovate" and "create". But no innovation and creative process comes without confronting our shadows, and education pays scant regard to this. 

The essence of digital creativity - like the essence of creativity in general - is the breakdown that occurs as we dig beneath the interface and try to grapple with the raw bits of mechanism that sit behind it. It's a psychological struggle - what was working, becomes broken. Often communication and sometimes motivation breaks down as we feel our way in the dark. In this digital shadow land, distinctions become blurred, but in the process, new communications are produced which gradually reconstruct something. And even if what is reconstructed is little different to what existed before, the confrontation with the shadow changes us. 

Online communities are susceptible to fanatical control because they have no way of talking to each other about their shadows. To dig beneath the digital interface is to recognise that, not only are we made of one physiology, but our communications are mediated through a unified computational architecture which ultimately is created by that physiology. More importantly, it is not the only technological architecture that is possible, and ours is not the only feasible technological world. The shadow lurks at all levels: the social media shadows are reflections of the shadows of each cell in our body. Our cells are rather better at dealing with their "shadows" than we are, with all our technology and communication. Understanding why and how is urgent - far more so than when Ivan Illich expressed similar arguments to politicise technology in the 1970s. That call has been misinterpreted: politicising technology is about getting technical.  

Social Media and Critical Sclerosis

Wanting to read endless critiques of the same thing - whether it's of education, educational technology, the pandemic, the war - is a kind of sclerosis. When we know everyone is basically saying the same thing, there are no new fundamental ideas, nothing constructive to address the deep-seated problems which lie behind the critique, then we have to ask "Why do we continue to look at this stuff?" There must be an explanation. Our (my) critical sclerosis is telling us something.

Double-binds are usually responsible for why we become stuck. The nature of the double-bind is that there is a contradiction at different levels of understanding, and then a prohibition on being able to articulate the contradiction. With "Critical Sclerosis" there is continual search for information - difference - in our environment. The reason why this occurs may be physiological and evolutionary: for some reason (about which there are theories) we are driven to continually seek out information about our environment. While we have become able to create difference for each other online (and desire to do this - so we share, tweet, etc), fundamentally our difference-creating operations are deceptive - the "boasting" online is deception - an intervention to get a reaction (think Trump). We deceive because we seek the information of feedback that our deception creates - it tells us something about those around us - so ties into the need to continually seek information. So the internet is a web of deception. It is interesting to note that those talking about the future of the web want to increase the deception with things like the Metaverse. This is unlikely to be a good idea! 

Selecting deceptions drains us of energy - fundamentally then, this sets up the first bind. We waste energy in articulating deceptions, and being drawn to reading them, which makes us more likely to make more deception. 

The second bind in the double-bind is easy: not only does nobody want to be called a liar (especially us!),  but even if we want to say "you're a liar", we are tempted to do it for the largest audience - i.e. online. But of course, to do that, is to posture and deceive in our communication. Unfortunately, academic status is something which is increasingly tied into this. If we really want to call out someone's deception online, then it must be done personally and intimately. This, of course, is very hard and emotionally difficult and will likely result in "unfollows"  and so closes-down the conversation. So the social media double-bind is very powerful - no wonder critical sclerosis has set in. What it means is that the variety of communications becomes restricted to those communications where the response is predictable by the community: "yes, I agree!". That's the sclerosis. I should hope nobody agrees with me, but of course I don't.  

There's a parallel here with Von Foerster's conjecture (see this brilliant paper: The unlikely encounter between von Foerster and Snowden: When second-order cybernetics sheds light on societal impacts of Big Data (sagepub.com). Von Foerster suggested that education and social systems tend to turn us into "Trivial Machines" - machines where the output is predictable from the input. The more trivial our communications, the more we are inclined to perceive our environment as overwhelmingly complex and alienating. I'm sure some element of this fits the double-bind of social media (as the paper discusses). 

But perhaps Von Foerster is too pessimistic about humans being capable of being turned into trivial machines. We are not really machines at all. Trivial behaviour is anathema to being human, and yet we do engage in trivial behaviour because we become sclerotic. We have sclerotic institutions and a sclerotic communication environment. What is at the root of the sclerosis but deception! The question to ask is why we deceive and what we might do about it. Technologies amplify deception, as does language. But some forms of communication are more authentic where empathy, kindness, generosity are expressions of the truth of relationships. Music does this too. 

In those more authentic communications, there is a healthier psychodynamic balance. Our non-trivial nature lies in our psychodynamics - the pull of the unconscious in our creative dealings with the world. In this terrible time, there is little doubt that we will need psychotherapy - not just the people of Ukraine and Russia, but all of us as we look to understand what has happened to us over the last few years. 

Depth Psychology and Computation

One of my favourite books, which I've known but not fully understood for nearly 30 years, is Anton Ehrenzweig's "The Hidden order of Art". It is a Freudian analysis of creativity, drawing on Frazer's Golden Bough, and inspired by Ernst Gombrich and Marion Milner. Ehrenzweig was interested in creativity through the lens of psychodynamic processes which connect the deep "oceanic" layer of the unconscious through processes of "projection", "fragmentation" and "dedifferentiation" where the ego and superego steer action into creative expression. With its Freudian lens, Ehrenzweig talks a lot about the experiences of early childhood and its influence on adult behaviour - particularly anal processes and the ways that the superego seeks to contain defecation, when deeper processes might seek (to put it crudely) to "scatter" shit everywhere. There is a parallel between these psychoanalytic terms and physiology - indeed, "dedifferentiation" has a specific cellular meaning where cells revert to their original states, which I think is clearly related to the Freudian view. 

I am aware of both modes in my technical creativity and in musical creativity - both relate directly to what Ehrenzweig sees as the dynamic between "containment" and "expansion". Death is an important driver for creativity. Ehrenzweig refers to Frazer's "Dying God", and in technical creativity, death is breakdown: the falling-away of established ways of being in the world, where the world as it really is is revealed once more, prompting our psychodynamic processes to reorganise themselves in response to it. Breakdown is one way in which one can descend into the oceanic undifferentiated world. Artists enter this world more willingly, being able to instigate their own breakdowns. But perhaps the sequence of processes which result is the same.

In technical creativity, the role of the superego is most dominant in ensuring that the organisation of the creative forces is socially acceptable and useful. It drives our intervention with software frameworks and established patterns. But not everyone wants to play this kind of game, and hackers are most interesting in getting at the underlying dynamics of established systems and looking for ways of disrupting them. I found myself hacking into the structure of programming documents in Jupyter notebooks the other day. The unconscious fantasy of self-expression and social transformation leads to fragmentation of the world. Moreover, the fragmentation of established systems can lead to fragmentation of the world for others. This is their intent. 

In these technical processes of creativity, there is energy - even when the superego has a tight grip. Fragmentation always brings new perspectives and the generation of possibilities. Even when I hacked the Jupyter notebooks, I was thinking, "wow - what could I do with this?". But at those moments of expansion of possibility, the superego still steps in and finds conventional exploitation of possibilities - usually within the existing social expectations of the society or business. But there is no reason why we could not create something purposeless - something which disturbs the surface of expectation. 

If there is a difference between technical creativity and artistic creativity it is that the dedifferentiation stage in artistic creativity, which finds a new unity and coherence among the scattered and fragmented components of the unconscious, is often missing in technical work. Instead, in technical work, the superego suppresses the unconscious drive to fragment and pull-apart - sometimes for good reason because technical things which are disassembled are difficult to reassemble. So what we have is a forced coherence and suppression which is often felt by those who use the results of this kind of technology. Indeed, Ehrenzweig goes so far as to suggest that there is a fear of dedifferentiation - of reintegration into the depths of the psyche: the psychodynamics is in some way broken.

It may be that the broken psychodynamic processes of technical invention are one of the reasons why we struggle to engage students in deep technical work or inquiry. Effectively we are teaching a kind of madness. But in those most creative periods of industrial creativity in the 19th and early 20th centuries, this was almost certainly not the case. There was dedifferentiation to some extent - and to some extent the rise of psychoanalysis was part of this process. 

In the wake of the terrible events that the world is experiencing at the moment, we may need to revisit a deep perspective on the technical imagination and its connection to the functioning of viable societies. Trauma and death have always been the seed for these healing processes. 

Personal Computational Environments: From Pedagogy to Technics

I remember when I first encountered R and RStudio about 8 years ago that I thought that this was a new kind of environment for learning. It was reminiscent of the Personal Learning Environment which I had spent so long thinking about (and which, in the end, didn't really amount to anything). RStudio appeared to be a "personal" environment for writing code, installing personal collections of functionality (libraries), being able to engage in a community of people who were doing similar things, and  managing a range of data sources. It was, of course, more technical and abstract. But it was obviously incredibly powerful - and it encapsulated one of the principle issues of the PLE - that a small set of technical tricks or dispositions could achieve a range of different outcomes: loading and running libraries, browsing CRAN, checking the documentation, manipulating dataframes, etc.  

A couple of years later, and it was the turn of Jupyter notebooks which now seem to have taken over. I know there are a lot of R enthusiasts out there who wouldn't be seen dead using Python, but python and Jupyter have become my go-to place for doing almost everything on the computer. It is the same story - a small set of technical libraries and a wide range of potential results. When I was in Liverpool overseeing the roll-out of Canvas, Jupyter was a go-to tool for accessing the Canvas API, getting data, analysing it and producing reports for management. It all worked, and it meant I could do "voodoo" in the eyes of colleagues who were otherwise helpless with anything apart from Excel.

It's obvious that these skills are important - and it's equally obvious that to a large extent they are unknown to most teachers, and not taught to learners. And this becomes a problem. Which is why I took a position in Copenhagen to work on a project to instil "digitalization practices" in topic teaching. I've had an interesting year (and I left Liverpool at a good time, having sorted the Canvas roll-out in just over a year - thanks largely to the data analyses. Once Canvas became established it was obvious that not much more was going to happen: learners and teachers couldn't actually do much more than they could in the old cludgy Blackboard)

The Copenhagen project has been challenging - which is what I wanted. As is often the case with these things, the real problems lie in the specification of the project itself. But it is good to have challenges to do difficult things - particularly if they are worthwhile.

I ended up with a small group of chemistry students plus a couple of students from my Russian university (Far Eastern Federal University) playing around with Python and OpenAI. This was an eye-opener - because OpenAI provided a  way into understanding the importance of Python without needing to explain all the computer science rudiments (variables, loops, etc), but instead just treating it as a kind of short "text" which, when run, did amazing things. I've now done similar things with the Russians on a larger scale, and with students in Germany. It seems to be the same story. If there is a rule to this, it is that we need to do things which have a relatively low technical barrier of entry (so a short "text") but which generate vastly more variety. If you can do that then the path into programming becomes clearer.

Today I did something with the same group that was not so easy. I wanted to store the generated OpenAI data in one of Tim Berners-Lee's "Solid" data stores. That should have been a lot easier than it was. And because it wasn't easy, and sometimes frustrating, I lost the students I think. There wasn't the "return" in terms of the increased generated variety. Even introducing the students to the power of the Linked Data that sits behind this, and its relevance in things like DBPedia, didn't really grab the students.

AI has the property of being able to return more variety than it is given. Agent-based modelling and automata may be able to do the same thing, or possibly visualisation tools. But this is a requirement for the pedagogy.   And in fact, my initial interest and enthusiasm for R was also the product of this rule: it was the realisation that a simple command to install libraries meant that the variety of possibilities of the platform was infinite. Of course, I would have to know something about the platform to realise that, but this is the point: we have to start from the position of a tiny amount of interest, and quickly produce a lot more variety which stimulates that interest. The AI-driven art tools are similar: Wombo dream is amazing, and can keep people captivated for ages as they type in different texts and observe the images that are formed. 

This is what it was like to be a kid in the early 80s when home computers were appearing. The generated variety of machine enticed because it meant that kids could do something that was more powerful than anything their parents could do. In my experiments with students, it seems the AI is having the same effect on them. After some familiarity, then you can do things with getting stuff on the web (we used Heroku), and that is another moment where the possibilities explode. 

So is there a way of structuring a pedagogy of technology that can fit a wide range of interests, disciplines, abilities  where the rule that whatever is done generates high variety, while making low technical demands? This would be to think of computing by starting with pedagogy, not with "topics", or even tools like Scratch. 

When Papert developed LOGO, he was thinking about the physiology of discovery, and trying to counter the essentially disembodied abstraction of code. Unfortunately LOGO, and Scratch, quickly become quite abstract, despite the fancy graphics, and succumb to a "curriculum". But what is really going on is a variety generation exercise: the turtle which draws elaborate patterns from a few lines of code. 

If we think about the variety first, we would not start with variables, loops and conditions. We would look for those steps to expanding possibilities from current technologies which empower individuals to do things which others who don't know the technology, can't do. So it could be:

OpenAI -> Flask -> Heroku -> GitHub -> ?Docker... I guess there are other possibilities (I've done all of these with the students apart from Docker - but I'm tempted to go there next).  But perhaps the specifics don't matter - it's the management of variety. 

The motivation to learn technical skill comes about through our hunger for greater variety. We need to design our pedagogy from this principle.