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. 

Rethinking Growth: is it really about things getting bigger?

I had an interesting discussion with biologist John Torday yesterday about mitosis - cell division. Growth is such a fundamental category in biology that it is easy to draw assumptions about it: the reason why cells divide is to reach out further into the environment; the reason is to survive; the reason is so that the cells differentiate; the reason is to generate redundancy; the reason is because "life is growth"... etc. But if you were sitting on the boundary of cell, why would you decide to split and divide so that all of sudden there are two cell boundaries?

Part of the answer to this is that you might decide to split because the boundary you are sitting on is unstable. It might be unstable because the environment in which the cell is attempting to survive in is uncertain or ambiguous. But why then would division contribute to a better way of managing that ambiguity or instability? Wouldn't it just amplify it? 

This is the critical question, and the answer to it leads to a new way of thinking about growth. Because division doesn't create another boundary; it creates a relation between two cells. Growth is the conversion of a single boundary into a communicative process which provides new dimensions of variation, stability and observation: each cell becomes an observer and communicator with other cells. Increased variety equips the two-cell system with better equipment for managing the complex of the environment. But only so far: more division is necessary, so new cells further divide, further increasing the variety.

This increased variation has a particularly important property and advantage over a single cell: the two-cell communicative relationship provides for the construction of an anticipatory system. The cellular communication dynamics give rise to a higher-order selection mechanism which steers the cellular communication. The growth of this mechanism also suggests that at some point, there is a limit to the need for further sub-division. This limit is real, and known as the Hayflick limit: human cells can only divide and replicate between 40 to 60 times (Hayflick limit - Wikipedia)

Reflecting on this, the two key points that: 

• growth through division is the creation of relations and communication
• growth is limited

Suggests that our understanding of growth in other areas of life is also wrong-headed. Even movements like "limits to growth" misunderstand growth, seeking to suppress growth in various ways. Evolutionary economics, in the light of "Unified Growth theory", and "Endogenous growth theory",  has the same problems. They all concentrate on the "mass" that is growing, and not the relations which are created in the expanded entities which emerge. There is a need to understand growth from the biological facts. Growth is the creation of observer-relations in order to survive in a complex environment. The "cancer" that is growth beyond limits is a positive feedback mechanism where amplification of the complexity of the environment causes new relations to be continually generated. 

The Hayflick limit must be a point of stability: a point at which the local variety of the multi-cellular system and its non-local environment is in equipoise. That stability will arise from and depend on the evolutionary history of each cell, and the collective niche-construction that their communicative processes produce. Of course, different processes of growth will occur in different types of cells, and there will be communication dynamics between the different entities which are formed. But these are then higher-order levels of homeostasis in the organism. The dynamics of growth are punctuated by stabilities.

In our unstable world, it is these stabilities that have gone: what Stafford Beer called the "relaxation point". The reason why lies in the communication dynamics of those original cells. At a certain level of biological organisation, cells in seeking their best route to survival, may seek to deceive other cells. This is a fundamental and important mechanism of biological development.  But a bad habit. 

With our brains and our language, deception becomes something else entirely. No longer a means of survival, it becomes a means of control. The flow of energy of the biological system gets blocked and bloated in the social system. This causes more uncertainty, and in turn, it drives growth beyond limits. The need to understand biology's limits of growth is urgent if we are to understand what is happening to us in the social realm.

 

An AI-generated post on "A Physiological Notation for Music and Learning"

I'm slightly puzzled that I haven't written anything in my blog for a couple of months. I've been deeply immersed in two projects - both of which are concerned with AI. In Copenhagen, the curriculum digitalization project has taken a fascinating turn in becoming more student-focused, and we are developing some new tools which will allow us to get a rich picture of how students see their future and how it relates to their topic studies. The other project concerns medical imaging, and this is now at an advanced stage of commercialisation and patenting - all of which is new to me. This is a fast-moving field, and it's giving me a lot of intellectual energy, but also keeping me busy.

One of the implications of the AI work is that the ability of the Transformer AI tools to generate text has reached a stage where it can present new ideas,  continue conversations, and provide a genuine stimulus to creativity. With some students in Copenhagen and in the Far Eastern Federal University in Russia, I've been working on a thing which I call a "meta-curriculum toolkit". It's basically a kind of google search which uses AI to suggest completions to a search term. The rest of this post has been generated by this technique:

A Physiological Notation of Music and Learning

I am interested in a physiological notation for piano music. I want to find a notation that directly translates into the body. While writing, I can feel a sort of body memory. I want to study this experience. I want to see if the notation that my body remembers can be presented as sheet music. A physiological notation for music would be powerful because it would allow us to be more specific about the types of information in a musical piece than verbal language is able to do. Conveying how a musical piece makes us feel would be a simple matter of listing the relevant physiological events: for example, elevated heart rate, increased respiration rate, dilated pupils, and so on. The association of music with the body in the mind of the listener means that the notation would be able to represent how a listener feels, not just what they think. 

A physiological notation of music would be an analogue of the language of the emotions which we have in ordinary speech. It would be based upon a notation of physiological action, rather than upon a notation of sound. If a composer could express the emotions which they wish to convey by the notation of physiological action, it would be easy for them to communicate ideas to other people. They could not only show them what they feel and think, but how they think. The connection between the emotions and the muscular actions which accompany them is so intimate and universal that it is a surprising thing that not one single author or composer has ever suggested that the whole of music should be played by means of the movements of the whole body, since these are the natural expression of the emotions.

If a physiological notation of music is an analogue of language, why can't we have a physiological analogue of learning? Learning is a form of change in the body, and it is the body that is the physical basis of music. If we can find a way to physically study learning, we can have a physiological analogue of learning. The body creates music by changing in response to sound and light stimuli. 

In Papert's original work on Logo, the physiological basis of learning was very important. Children were meant to play with physical turtles and discover mathematical concepts. While the physical objects were an important part of the learning process, they were not the learning process. The ideas were the focus. Any user of Logo must learn a new vocabulary before using it. This vocabulary is, however, based on mathematical terms. As educators, we have to be careful about how we use computer technology in the classroom. It is very easy to focus on the technology without thinking about what we are doing or intending to do. 

An idea - the emergent ideas in learners - is rooted in physiology. The notion that the brain is the seat of all mental activity is a bundle of uncorroborated assertions. The idea that the mind can be divorced from the brain is a belief, not a fact. The idea that the human mind is a computer and the human brain, a computer-like device, is also rooted in a belief, not in scientific fact. and minds. Ideas sit in the cells of our bodies. They can be triggered by events or insights from others, but they’re also waiting for us to look at them and pick them up. This is why the idea can feel so familiar, just like something we’ve always known. We have to do that work in order to recognize our own ideas and make them real. The idea, the motivation, and the action are all essential parts of this creative process.

 

If learning is physiological, then finding a way to notate the physiology of learning would be an important development in education. It might open up a whole new approach to teaching and learning, one that is more natural, more holistic, and more powerful. What would such an approach be like? It would be like music.  

 

On Smartphones, Sandwiches and Teddy Bears: Energy flow in the Academy

I had an interesting discussion today about the nature of technology. It partly revolved around Latourian interpretations of agency, with the kind of criss-cross of concrete examples and theory which is particularly enjoyable when talking about technology. The "is x technology" game is fun, and its associated "does x act in a network?". It's perhaps defensible to play this game with a smartphone or computer, but harder to consider these questions with the concrete examples of food or teddy bears. 

Does your carrot act on you? Is your sandwich technology? Is this even a useful question? Well - it is if it exposes some fundamental weaknesses in social theory to which we are otherwise blind, and which if overturned, changes our perspective on other categories of understanding. 

In Latour's work, the sociomaterial co-construction of tools and humans arising through the emergent interaction of human and non-human "actors" is pivotal to an analytical approach which seeks to map out these networks and their dynamics. It's an idea which relates partly to systems-theoretical, process-oriented ontologies, and to mapping techniques which have become increasingly available in the wake of computers. 

I've never been particularly comfortable with the concept of "agency", and particularly with the concept of non-human agency. Apart from anything else, what is conceived as non-human agency seems to be really human agency at a distance. But then there is a question as to whether one can even draw a distinction around human agency itself. To what extent is the concept of agency meaningful - when do we "not-act"? Is thinking agency? Even when people's physical liberty is constrained,  they are still able to think. Anna Akhmatova's composing of poems in her head, committed to memory for fear of writing anything down, is agency, isn't it? 

For a number of reasons, I wonder if "energy" may provide a better way of thinking. It is useful to think in terms of energy because when education loses energy, it is not very good - irrespective of the agency involved. Moreover, when we act, we are involved in some kind of "energy exchange": Akhmatova's organising of her poems required energy in her body; participating in a conversation requires energy; depression and other mental health problems drain us of energy; and all educational development is the realising of "potential".... do we in fact miss the word "energy" from that? Are we really about unlocking the "potential energy" for future transformation that could be exercised by a student?

Discussing controversial objects as "technologies" also present a further case for thinking in terms of energy. For example, is a sandwich technology? Irrespective of the fact that human agency is involved in its construction, what is a sandwich but a container of energy? The same can be said of a carrot (and ultimately carrots and sandwiches get their energy from the sun). I find this interesting because seeing a sandwich as an energy container then throws the spotlight on the eater of the sandwich. The seeking out of food, the moving of the jaw, salivation, etc all requires energy. This latter energy is physiological, which the energy in the sandwich is "potential" (for want of a better word). But this is not a "gaining of energy" by eating the sandwich; it is a transformation of one kind of energy (physiological) to another (the sandwich) which in turn becomes transformed by metabolism (another process requiring energy) into physiology. Across the interaction between eater and the sandwich, total energy is conserved, but transformed from one form into another. The sandwich is a transducer.

What about a child's teddy bear? That is even more interesting I think. My daughter raised this with me when she was about 6 or 7 (she's now 21!). The child's reaction to her teddy bear is to expend energy on it: she hugs it, maybe talks to it, is concerned for it, she invents a world for it to exist in. She draws an imaginary distinction about the teddy bear as a "person" in her life. So what is happening energetically? It is as if the teddy bear is transforming energy within the child. Hugging requires the expense of energy. But what is gained is epigenetic information about the environment. The smell of the teddy and the release of oxytocin (the "hug hormone") are all critically important features of this interaction. It is an energy transformation where energy expended by the child is made and energy in terms of information is returned. The results are new distinctions, new actions, new (imaginary) conversations - and indeed some real conversations (when the parent asks where the teddy bear is). 

In the philosophy of Gilbert Simondon, all technologies are transducers. They exist at the boundaries of our interaction with an uncertain environment, what Simondon calls the "margin of indeterminacy between two domains ... that which brings potential energy to its actualization". Moreover life at all levels is made up of "margins of indeterminacy": it is the relationship between cells in their extra-cellular matrix, or the functional differentiation of the organs of the body, organisms in an epigenetic environment, the boundaries of social institutions, the interfaces of technologies, or concepts of personal identity. And the point about technology as transduction is that this "interface" that I perceive between myself and my computer is a process of energy conversion which is connected to every other process of energy conversion in my body and the universe. 

The physicists tell us that energy is conserved. They also tell us (at least the Quantum Mechanics people) that there is a dynamic balance between local and non-local phenomena. What happens at the boundary is a transformation of one form of energy into another which amount to the same quantity: the total energy in the system is preserved. In biology, we may see this energy transformation in the form of a balance between the energetic processes inside a cell which lead to protein production by DNA, alongside the epigenetic environment of the cell and its communication and organisation with other cells. It is the cell boundary which serves as a transducer (which is of course, exactly how the cell biologists describe it: Transduction (genetics) - Wikipedia)

Transduction is both the process of converting energy from one form to another, and the process of identifying the boundary across which transduction occurs. Thought generates transducers in the form of concepts. Akhmatova generated her poetry in her head, and as she did so, she created herself - what Simondon calls "individuation". Is there any real difference between the transducers in our heads, our concepts, and the transducers we type at and browse the web with? I doubt it. Gordon Pask was probably the first to think this: he saw concepts and objects in a very similar way - the results of self-referential processes, what von Foerster called "Eigenforms". Simondon's transduction is very similar. 

What this means is that we are looking at technology wrong. If we see tools as "objects" we will miss what is actually happening, and if we fail to understand what is actually happening in terms of energy, we will not be able to control effective energy flows. That is basically what has happened in education and technology. It is (yet another) explanation for why Zoom education is usually crap! It also helps us to explain what happens when we become "addicted" to social media: transductions can be highly inefficient, creating demand for more engagement which in turn is increasingly unrewarding.

However, if we see energy manifesting and transforming in human relations through tools, language, interfaces and even sandwiches, then we can gain better and more effective control of ways in which the "potential" (energy) of every individual in education can be realised. 

Digital Endosymbiosis

Digital Endosymbiosis is a realignment of universals and particulars between the activities that take place in an institution and those which take place outside it. At the moment, disciplinary discourse is confused about what is particular and what is universal. One has only to look at the critical discourse to see the identification of "pathology" in various areas (obesity? bullying? global warming?), with little attempt to see that all pathologies have the same structure with specific realisations. As the tools we use to teach become better and more refined, the underlying patterns of universals will become increasingly apparent. However, I think it is likely that these tools will emerge inter-institutionally because this will be the most effective way that institutions can realise their plans to "digitalize" the curriculum. 

This seems to be what's happening in Copenhagen, where I think real progress has been made on our digitalization project (steering collective understanding of something nobody understands is hard - but we're getting there). Also in the last week, I have been running the Global Scientific Dialogue course in Vladivostok, which will feed into an inter-institutional initiative from the Russians in the form of a Learning Futures Laboratory. I see no reason why these things shouldn't come together. Meanwhile, just to remind me of how current institutional arrangements are not viable, also this week I have been in some pretty intense negotiations with my former university about intellectual property and potential commercialisation of a project I have been involved in for 5 years.  Everything seems to happen at once. Having said that, it may all be quite good in the end.

The Global Scientific Dialogue course was excellent - again. This year I did much more around technical skill - it really is a course that is tool-led, rather than content-led - and the tools I introduced the students to included AI, Google colab and P5. All of this is framed around asking "big questions" about the future, wicked problems, etc, for which they work in small groups supervised by a team of 20 teachers. I was worried I had lost them because I tried to do something quite ambitious with Python generating word-clouds with the students own data. Actually, it turns out that many gained exactly what I'd hoped: "programming is not so easy, but it is really interesting, I realise I can do it, and I want to know more". In a course for people many of whom have never programmed before, you can't hope for more than that. And there was a remarkable moment when those students who were more experienced effectively "took over" the class to help those who were struggling, each student sharing their screen, and other Russian students talking them through how to fix their problems. I've never seen that before online - it was like "Twitch does programming". 

In Copenhagen there's been some tension around whether digitalization is about changing the curriculum (and so developing more technical skill in students), or if it is about changing teaching. It is, of course, both. The problem we have in teaching in institutions today is that all our technology has been taken over by industrial concerns. This is the deep reason why education has become increasingly transactional - the industrial systems we use are transactional. I've hatched a plan to challenge this by developing new teaching tools in-house which invite students into a collaborative process of making those tools better, and so are introduced to the technical discourse outside. Moreover, this improvement process can be done inter-institutionally. Vladivostok, Copenhagen and Liverpool might be my first pilot users.  It means that institutions can start to build a technical niche for themselves in a shared environment which connects them more directly with the world outside. Without getting carried away by this, it may mean that in the fullness of time, the inter-institutional niche becomes the main focus of educational activity, with institutionally-bound activities become more specifically focused on deep conversation around disciplines and research. I see it as a kind of institutional endosymbiosis - universals outside, particulars inside. 

I think if there's a thread that runs through everything it is that the internet will eventually transform the institution of education in ways that it clearly hasn't until now. It won't be about online classes or any other online reproduction of the traditional academy. It will be about the necessity of every individual to adapt to the digital environment as it is actually unfolding, not as institutions teach it. This necessity will mean that something will happen between institutions, not inside them. The institution will not die, but it will change into something other than what it is at the moment. As tools for teaching different subjects are refined, it will become increasingly obvious that our tools reveal the commonalities between our disciplines - universals. Beyond the development of deeper tools for inquiry, the need is for institutions to to conduct the conversation about particulars. This is what I suspect the disciplinary discourse will turn into - much more about the discovery of special cases in nature or society - a critical movement which feeds into the ongoing refinement of our universals. 

Energy Collages in Vladivostok

When I went to the Paula Rego exhibition in London the other month, something really struck me about what Rego said about her technique of "collage". She talked about the sensual energy of tearing into something - pulling things apart (I can't remember the exact quote). My own experience too has suggested to me that there is something about tearing things apart and reassembling them. In the Global Scientific Dialogue course I've been running in Russia this week, collage and energy has been something of a theme: breaking things and fixing them. Today the students made collages from objects they found around them (inspired by Andy Goldsworthy). I'll post some of their images when I have permission from them. Yesterday, I made the  connection between tearing things apart and getting "stuck into" coding - breaking code and fixing it. There's more to be done with this, but it's all very promising. 

A lot of our social media is a collage. That is basically what a Facebook or Twitter "feed" is. It has an energy, and the continual rearrangement seems to keep on regenerating this energy. Is this why we find it addictive? Of course, its not unusual for "cheap" sources of energy to become addictive... that's what keeps McDonalds and Coca Cola in business, after all. The energy of the collages we make ourselves is hard-won; the breaking-apart of things is a real agony, and the rearrangement is a discovery. This is where the learning is.  

I've been reading Simondon's "Individuation in light of notions of Form and Information". There's a lot of stuff about energy there - both in physics and biology. Simondon goes back to the Aristotelian idea of "hylomorphism", critiquing the basic concept that in order to have any kind of "stuff", there must be some ideal form of the stuff to begin with. Hylomorphism was a doctrine to explain how it might be possible to get "something" from "nothing". The "idea" behind the thing was a way of explaining how this might happen. 

Getting something from nothing is a problem that has preoccupied physicists for most of the 20th century. If there was a "big bang" for example, where did that come from? Is a singularity something or nothing? 

I have been fascinated by Peter Rowlands's work because he turns this question around - it's not about "somethings" at all - everything is in a process of making successive "nothings". The algebra to support this idea derives from Hamilton's quaternions, and using this, it is possible to show how Einstein's mass-energy-momentum equation is really a Pythagorean triple, which factorises to zero.  But more basically, if everything is about nothing, and it is nothing which drives the process of creation in search of nothing, then we have no need for hylomorphism. 

But we do need energy. If E = mc^2, or rather E - mc^2 = 0, and this can be factorized into two expressions which represent "local" and "non-local" physical systems (whose product is nothing), then it might be possible to see how "tearing something apart" releases energy - the E in the equation. All as part of the continual process of resolving the tension between local and non-local to zero. 

Is this the driving force behind biological systems and learning? Does this explain why we are curious to know more? Cell division is, after all, a cut in the system - the creation of an asymmetry, rather like the tearing into a picture to make a collage.  Consciousness sits on cell division and self-organisation, local and non-local factors are mirrored in the relation between DNA and epigenetic marks. 

The mark of learning is to tear into things - to break things as a way of seeing things new. In Vladivostok I hope I have been there to support people doing this, and maybe in a few cases, to pick up the pieces when the shock of breaking something is too much. 

Technology has no Curriculum (How to teach fish about water)

If there is a central tension in the wrestling match between technology/digitalization and Universities, it is that the curriculum is the central pillar of educational organisation, and the web organises itself quite differently. The online world is the epitome of self-organisation - it is no accident that the systems theorists whose work gave rise to the technology also produced the constructivist epistemology which described how natural systems needed no rigid blueprint for their development. 

Education's "curriculum-blinkers" means that education "schoolifies" the world: everything it encounters in the environment must be boxed-off with learning outcomes, a course plan and a timetable.  If this cannot be done, then basically education can't deal with it. The problem can be described in systems terms: it is basically a problem of "requisite variety".

Education works by attenuating the environment (the world) into organisational structures whose fundamental purpose is to coordinate conversations and award certificates. Education has lower variety (complexity) than the environment, but because it also creates an important part of its cultural environment in the world (it creates a niche for itself), it is able to maintain a stable existence in a complex world: it has "requisite variety". Niche construction takes many forms, but includes creating criteria for certification which can only be offered by education, professionalisation, producing artificial scarcity of knowledge and learning opportunities, creating "failure" and "success", and enculturing the young from birth into the habits of formal education.

This process of education's niche construction has depended on the world being "schoolifiable" without too much loss of information about reality. Technology threatens this. As much as the champions of digitalization try to persuade us, technology has no curriculum. It is essentially and irreducibly transdisciplinary. Of course, we can teach those aspects of "computer science" that encapsulate some of the skills and techniques of using technology, but this is only a small aspect of what technology is, what it does, how we should think about it, and what we might do with it. 

Heidegger called the essence of technology "enframing" in his famously pessimistic but penetrating essay on technology ("The Question Concerning Technology"): enframing was a kind of encapsulation of the thinkable world, rather like Blake's "mind-forged manacles".  Being the reactionary idealist he was, technology led him to want to escape into a world of poetry instead, which he saw as offering a different mode of encounter: what he called "dwelling". But this is the same Heidegger who saw that the future of philosophy lay in cybernetics. His own struggles mirror the struggles that education is now having in dealing with a world that simply doesn't fit its conceptual scheme. 

Heidegger knew he was struggling to deal with conceptualising something that resisted conceptualisation. He was a product of a traditional education system. Little wonder technology troubled him so much. Those thinkers who came from rather less conventional backgrounds like Illich had a better grasp. Technology, rather like time, gives us nothing to get hold of in the conceptual frame from which we inspect it. Our organisational structures can't grasp it. And yet, in our daily practice, our industrial practices, our communications, our creativity, our concerns about what is right and wrong, we are all swimming in it. If fish had universities, would they be able to teach them about water?

All this is telling us that our curriculum-based practices will eventually have to give way to a different way of organising human development and organisation. And yet, say this to anyone in a University and they will look at you as if you are mad. But look at what is on the horizon. The noise the technology companies are making about the future of education, and the enormous sums of money that are being invested, is mostly hot-air and greed - but not entirely. 

In evolutionary history, the most flexible and adaptable organisms survive. So compare a university (any university - they're pretty much the same) with a company like Microsoft or Google. Which is more adaptable? Which is more flexible? 

This is not to say that Google's current pitches for the future of education are the future. They are unlikely to work. But they are playing a long-game. Many of our current technologies would have been considered science fiction 30 years ago. We cannot begin to imagine our technological environment in 30 years time. But preparing for the future is what adaptive organisations do. 

Companies caught in an "adaptation block" are now developing separate branches free from the constraints of conventional business organisation. Universities need to be doing this.