Health and Self: Education, Positioning and AI

I've had an exhausting week. But it's also been a very good one.

This week, we've welcomed a large group of staff from an international pharmaceutical company to the university. We've been working with the company for the past year on a project that engages university students with real organisational challenges within the business. It's been an opportunity for genuine innovation, both in the use of AI (although in a rather unusual way) and in the coordination of understanding between students and people working in the company. The whole experience has been a huge success.

But, of course, it's also been exhausting.

By the time Friday arrived, having also taught a large class on epidemiology, I had very little energy left. My approach to managing large classes has increasingly involved combining face-to-face teaching with small, online sessions that are deliberately dialogical and conversational. I must confess that, having reached Friday feeling completely knackered, I wasn't particularly looking forward to three short online meetings with groups of students.

And yet something remarkable happened. Or perhaps not so remarkable, because I've experienced it many times before.

In these meetings, we talked about the things the students were interested in, their ideas about their assignments, and their reflections on the activities we'd undertaken in class. By the end of the conversations, my mood had completely changed. I felt energised, enthusiastic and considerably less tired.

I've experienced this before, often in online conversations with fellow academics with whom I regularly discuss our deeper interests in biology, physics, mathematics and other subjects. These conversations, too, invariably lift my spirits.

Why?

Positioning, communication and the emergence of self

On reflection, I think these experiences confirm a theoretical perspective I've been considering for some time, particularly in relation to the work of Rom Harré.

Harré's positioning theory offers a useful synthesis of several traditions in the study of communication and human interaction, including Erving Goffman's work on the presentation of self, J. L. Austin's speech act theory, and elements of depth psychology.

At the heart of Harré's argument is the idea that the self emerges through dialogical relations. Communication involves speech acts: selections through which we do things with words. But these acts are always contextualised by positions: the shifting relations of rights, responsibilities, authority and power within which individuals find themselves. Speech acts and positions also acquire meaning through storylines: the narratives through which people understand what is happening, who they are, and how they relate to others.

Positioning is therefore a dynamic relationship between speech acts, positions and storylines. None of these can be adequately understood in isolation.

What interests me particularly is that positioning theory appears to involve different dimensions of communication and, crucially, interactions between those dimensions.

I've been exploring similar distinctions in other contexts, drawing on Shannon's information theory, Luhmann's theory of communication and geometric algebra. I wonder whether we can understand a speech act as something like a vector: a directed communicative selection. A position, meanwhile, entails relational constraints between possible acts and participants, suggesting something analogous to a bivector. The storyline involves a further order of coordination: an individual's understanding of themselves in relation to others and their anticipation of how those others understand the situation. This suggests something analogous to a trivector.

These are not straightforward mathematical equivalences, of course. Rather, they suggest a way of thinking about communication as involving dimensionally distinct but interacting relationships.

The important point is that communication isn't simply an exchange of messages. It involves the continuous transformation of the relations within which those messages become meaningful. And, as those relations change, so too does our understanding of ourselves.

Why did talking to students make me feel better?

This brings me back to Friday afternoon.

Harré's argument suggests that our sense of self emerges through the dynamics of positioning. Learning, in turn, involves changes in positioning that can transform and deepen that sense of self.

I think this helps explain why I felt so much better after talking with my students.

Those conversations changed the positioning of my own communication. I could perceive the difference that I was making to the students. But, perhaps more importantly, the students could perceive the difference they were making by articulating their interests, exploring their ideas, questioning assumptions and discovering new possibilities.

Their contributions changed the conversation. They changed my understanding, just as I was contributing to theirs.

There was a mutual transformation of positioning, in which each participant could recognise their own agency through the responses of others.

And that is deeply enlivening.

It suggests that the energy we derive from conversation isn't simply a consequence of social contact or the pleasure of talking about interesting things. It arises from something more fundamental: the experience of making a difference to another person, recognising that difference, and experiencing our own sense of self changing in the process.

From students to consultants

My work with the pharmaceutical company this week has been similarly energising, and I think for essentially the same reason.

The students involved in the project had become sufficiently attuned to the company's needs before its representatives arrived that they were able to exercise real agency in the subsequent discussions.

Something fascinating happened. The positioning between the students and their corporate counterparts changed. Rather than simply being students responding to a problem set by a company, they became, in effect, the lead consultants in the solutions they were developing.

They had something valuable to offer, and the company recognised it.

Their expertise, their confidence and their capacity to make a difference were transformed through the interaction.

For me personally, there was something similar going on. My role in creating the conditions for this transformation became visible to others, including those more senior within the university. That recognition also changed my positioning within the institution.

I don't think these experiences are separate. The students' transformation into consultants, my own experience of institutional recognition, and the remarkable improvement in my energy after Friday's online conversations are all manifestations of something closely related.

They concern the way our sense of self is shaped, sustained and transformed through our capacity to make a difference within relationships.

And I think this is something we need to consider much more carefully in education.

The problem with AI and dialogue

The role of technology in facilitating these transformations of self cannot be overstated. Yet I think there's a serious danger that much of the current discourse about AI in education is getting hold of the wrong end of the stick.

Many educational scholars have become fascinated by the apparent dialogical relationship between humans and machines.

This fascination isn't new. It may be another manifestation of a longstanding obsession with mimesis: the creation of something artificial that imitates human life or intelligence. We can trace versions of this fascination back through centuries of mythology, including the legend of the Golem.

But I think this focus misses something fundamental.

The important dialogical relationships are not those between humans and machines. They are those between humans.

Indeed, I would argue that the relationship between a human and a machine is not properly dialogical in the sense that Harré describes. A machine can generate responses, simulate conversation and participate in linguistic exchanges, but it doesn't occupy the same kind of socially constituted position as a human participant whose sense of self, agency and responsibilities are transformed through the interaction.

The more interesting question is therefore not whether AI can converse with us, but how AI changes the conditions under which we converse with one another.

What does the technological context contribute to the formation and transformation of human relationships? How do these new language-based technologies change the positioning of teachers, students, employers and institutions? How might they increase our capacity to understand one another, to recognise one another's contributions, and to perceive the differences we can make?

These, I think, are the really important questions.

Our work with the pharmaceutical company offers one illustration. AI has helped us coordinate understanding across institutional boundaries: between a company with its particular organisational challenges, a university with its educational responsibilities, and students with their developing knowledge and capabilities.

The innovation hasn't principally been in getting people to talk to AI. It has been in using AI to transform the conditions under which people can talk meaningfully to one another.

And this has created opportunities for entirely new forms of agency, learning and collaboration.

Education needs to change

It seems obvious to me that these technologies have enormous potential to accelerate the coordination of understanding between students, teachers, employers and institutions.

It seems equally obvious that this is the direction in which education should develop.

Yet this is radically different from much of what remains embedded in educational theory, institutional structures and everyday pedagogical practice.

We continue to organise education primarily around content: its production, delivery, acquisition and assessment. Our institutions are structured around curricula, learning outcomes and mechanisms for demonstrating that specified knowledge has been transferred.

Relationships tend to be treated as the means through which this process happens, rather than as the central phenomenon through which learning and the development of self actually occur.

But what if we've got this the wrong way round?

What if the most important educational outcome isn't simply what students know, but how their positioning changes? What if learning is fundamentally about expanding a person's capacity to act, to make distinctions, to contribute to the understanding of others, and to recognise the difference they can make?

And what if the most important contribution of AI to education is not the automated production of content or the simulation of a personal tutor, but the transformation of the relationships through which people come to understand themselves and one another?

I think my experiences this week offer a small but powerful illustration of what this might mean.

On Friday afternoon, I began three meetings exhausted, wondering how I was going to summon the energy to get through them. I finished feeling more alive, more engaged and more enthusiastic about my work.

The students hadn't simply received something from me. We had changed something for one another.

That's what education can do.

And it's what our technologies should help us do better.

Logic and Emotion

When I was a teenager I was obsessed with the relationship between logic and emotion. I don't think this kind of obsession is that unusual among teenagers (I've seen it many times in others although school knocks it out of them!), - it is a sign of the sensitivities of adolescence and how our fiery brains tackle the mysteries of consciousness and rapidly shifting hormones. I haven't quite left this stage of my life behind though... Which is something I recommend to my students - keep hold of "young ideas"!

I've recently been making some unusual software which relates verbal communication to musical communication (if music can communicate... I would tend to say it coordinates emotions). It uses the same Shannon entropy techniques that I learnt from Leydesdorff and applied them to the interplay of concepts communicated verbally. It visualises these interactions nicely and it gives me a lot to think about.

Most people think we coordinate our understanding through the exchange of words which are the index of coordination. There's a whole field of applied linguistics which focuses on the use of words to establish rapport, etc.  I don't think this is quite right (and in fact the extent to which it is wrong underpins a lot of pathology in organisations). To start with, it's not words, it is concepts... but it is not so much our articulation of concepts as the ways in which we reveal our ability to manipulate concepts. Which is pretty much what I've done on this blog for nearly 20 years. What we tune into is each others agility in moving across a conceptual field. 

My new software is able to measure this. Which is cool and fascinating. It makes me think that we are barking up the wrong tree with large language models, although they are useful for moving towards a much more powerful coordination technology. 

The key question about agility is not to determine the agility of conceptual shift, but to understand the fundamental springs which govern the dynamics of the shift in the first place. I'm pretty convinced that such springs exist, and that our ability to ignore them is the root of so many problems. It is the difference between Keir Starmer's communication skills and Andy Burnham. Burnham is "natural" because he is more tuned-in to these dynamics.

We need more people to be able to do this, and it may take a technology to help them. This would be a truly useful "artificial intelligence"!

Intangible measurement

I got an award for being a "pioneer" yesterday from my faculty in Manchester. It's principally for the AI stuff which I led. I feel a bit embarrassed because I tend to scoff at this kind of thing. But being on the receiving end of warm words by one's colleagues is a different experience and very meaningful. And these are colleagues who are dear friends. Increasingly I find my professional satisfaction comes from the immediate collegiality of the university, the department and my students. This constrasts with what we are told about academic achievement - the papers, projects, money, etc. Collegial support beats that hands-down in my view. The papers, projects, money tends to be bureaucratic, divorced from students, and often rather selfish.  

Of course being curious, thinking and reading are fundamental to any academic life. But the slightly shocking fact is that publishing and projects are strange kinds of game which should reflect curiosity and originality, but tend not to. There is an enormous amount of path dependence and groupthink in the system which pushes originality away. REF is partly to blame. What are we to do? Well, what we can do is to "pass the message on" - and that is what the collegial thing is really about. It's particularly powerful if we can pass the message on to our students - by changing their lives, the world is changed. By changing the thinking of colleagues new possibilities for collective organisation are created. 

Strangely, these intangible things are hard to measure - but it can be done, and I am deeply grateful to be the subject of some kind of intangible measurement. We should probably concentrate on doing more of this, and far less in the nonsense metrics of citations! 

Evolution is the preservation of contingency

There is a difference between prediction and regulation. I suspect also there is a difference between anticipation and prediction. An anticipatory system - which all biological systems are - does not simply make bets on the future. Of course they make choices, but in the process they remain open to contingency. Predicting machines do not do this. They make choices and throw away contingency. 

Evolution is the name we give to the ongoing process of maintaining contingency while making choices. Taken as totality, evolution is a process of regulating homeostasis, at the level of organism, species, ecosystem, universe. Exactly how this is done we don't know. Our AI systems do not do it, that's for sure. The many different biological theories (for example, Friston Free Energy) are deficient because they too discard contingency. 

Music is a phenomenon (or at least the human relation with music is the phenomenon) that does preserve contingency. Studying its mechanisms for doing this can perhaps help reveal how it does it... But we are a very long way from understanding it. It is analysable in terms of information flows, as I've argued many times, and in those flows, no information is discarded - every element of contingency is necessary in order to construct the conditions for closure of music. It is a highly complex evolving system whose evolution occurs in front of us, unlike evolution itself. 

But we do not live in a musical world. If we did, we wouldn't have so many problems. We live in a world of language - and language does not have the property of music. As St Anselm said in his "De Caro Diablo":

We ought not to be 
held back by the way 
in which the improprieties 
of speech hide the truth, 
but should rather aspire 
to the precision of the 
truth which lies hidden 
under the multiplicity 
of ways of talking

Music gets closer to the truth. 

I'm currently working on a project which tries to get beyond the improprieties of speech. I don't want to dismiss LLMs - they move the bar in terms of the realisation of new technical explorations in ways which would previously have been impossible (or perhaps improbable). But it is possible to explore the deeper music of language.. not it's sound, but it's dynamics. 

We use words to refer to concepts without really having a clear idea of what a concept is. But we can say a few things about concepts which sheds light on these dynamics. Gordon Pask regarded concepts as stabilisations in recursive processes (there's recursion in the idea of explaining concepts!) - more technically they are eigenvectors produced in the process of organising a cognising system in an unknowable environment. Pask saw the perception of objects no differently - "reality" is stabilisations of recursive circularities. The process of eigenvector formation is difference and similarity which arises in the multi scale conversational dynamics between actors. Another way of putting it is that in these processes we detect states and transformations. 

We can't know directly what drives these dynamics except that the words that we use and the concepts they refer to leave a "trace" which  challenges a biological system to adapt. When we analyse conversation we are analysing the adaptation to all these traces. The interesting question is what happens between one trace and another. The in-between moments of traces sees a dynamics of dealing with information and contingency. This is the energy of what is going on. These dynamics are very similar to music. 

Our present AI can help us get off the starting blocks to analyse this. But it cannot really help us harness the energy of language because it throws away information - it is a prediction engine. This is probably why the LLMs are not particularly practical in real life - present obsessions with them are likely to fail. The increased efficiency and productivity of organisations depends of better regulation of their operations. That in turn depends on conserving contingency. Where we are at the moment is we have AIs which discard contingency by making predictions, and meanwhile idiotic managers, transfixed by the technology, will further discard organisational contingency by replacing humans with robots. It's not going to end well. 

We are going to need a new kind of technology which doesn't generate language, but somehow helps us to feel language and it's organisational context more deeply. It should help us to feel the energy of speech. It should tell us how and when meetings are pointless and dull (as if we need telling!), or identify the energy of creativity, or spot the telltale signs of psychopathy. 

This technology will be useful, and more importantly, it won't replace people, but in fact enhance the potential of effectively organised human systems. That is what maintaining contingency really looks like.

"The Old Oak" and utopian nonsense

Astrid and I watched Ken Loach's recent (2023) movie "The Old Oak" last night. Don't know how I missed it when it came out. I admire Loach's work deeply because it reflects the world we are in in a way which preserves the grittiness of daily life, but retains the possibility of magic which is the preserve of art. 

The conversations among reform voters, aggressive and angry people, young and old, the disappearance of hope, and the sheer logic of their grievance needs to be set out dramatically. This is not abstract. No warm empty words from privileged classes - politicians, educators, philosophers - can possibly get close to the rawness and realness of emotion. However, there is space for intelligent analysis of the context within which the drama plays out - the role of social media in whipping up hatred, the dilemmas of people who cannot escape hypocrisy, the sheer fear of refugees whose traumas in the UK are just the latest stage in a litany of trauma.

I have academic friends who talk of how things are getting better, how technology will bring us together, how the education system can be fixed. What nonsense. Get them to sit in the pub with these desperate people and try to explain that... "Technology will revolutionise society and make things better!" they might try to explain. "For whom?" Will come the most polite of the responses. 

"The problem is we have a false ontology!". Fuck off! - people have got no money! 

I want to think not of causes - it's too complex, and yes, ontology is part of it - but it's practically impossible to have a conversation about that even in universities! Much better to think about how to coordinate interventions. There is no one-size fits all solution, although there may be an ontological root. But when there are so many needs and demands, and so much diversity, and there are so many possibilities for addressing them, how can we select and coordinate interventions. Most tantalisingly, might we be in a better position to do this now than we once were, given the technology at our disposal?

That's going to require some ingenuity. And much of it will not work. But if we can coordinate interventions better then there may be ways we can address these deep issues more constructively, and in way that fits peoples' real lives much better than we currently do.

Creativity tomorrow

I find myself in a transition phase at the moment. I've spent the last few years trying to wake academics up to what was once the "impending wave of AI", and spending quite a lot of time frustrated by the fact that most academics thought it was irrelevant. Now everyone's a sodding expert! Well, that's academia for you...

So I think I can back away from this AI mania for a bit and let people get on with it. My university has bought 60000 licenses for Microsoft copilot. Personally, I would have done nothing, but worked hard with the staff to accept that our educational environment has changed and we must change - but buying an AI platform is not the way to do that! The locus of control of technology must sit with the individual student (and academic) - even if that now amounts the locus of control of the cost of technology.

Management anxiety has led to the institution to take this decision. They want to be seen to do something. Others will watch and see what happens... "For god's sake, don't just do something - stand there!" would have been more sensible advice.

Of course what the institution won't be able to do will be to keep up. I attended a fascinating "creatives" session at the RNCM the other day. There were film-makers who are making a name for themselves with AI video. They liken the present situation to the rise of cheap sequencers and production software in the 90s which meant that kids in their bedrooms could make music that only professionals could do a few years before. That's now happening with movies. No need for actors, props, lighting, sound, etc. Artistic input is still there but it coordinates activity by "worker bots" rather in the way conceptual artists produce art with assistants. 

That's here to stay. We're going somewhere different now. 

Most fascinating is the ability to generate analytical dashboards based on real-time discussions. I've got quite good at this. I was in a meeting with a public health academic this morning talking about cooperative housing. While he and another friend were talking, I made an app to distil the parameters of the conversation and demonstrate the interrelations between them. Quite amazing - and they were a bit gobsmacked. 

Of course AI is not making any money, there will be a crash, the energy, etc. But the energy problem will be solved (as many other issues will be) - its like early steam engines. 

So on the one hand I'm backing out of institutional AI. But I'm moving forwards with AI. The institution will get left behind. But that may need to happen...

The Reality of Charles Ives

Charles Ives famously joked once "Are my ears on wrong?" His music has always confirmed to me that if his ears were on wrong, so were mine. I was introduced to Ives by my dad who once led a production of Waiting for Godot, and had found the perfect music to accompany it - The Unanswered Question. Curiously a few days after my dad died (many years ago now), I went to a concert (trying to clear my head), and there was a remarkable performance of the unanswered question in Manchester. Strange how those things happen - it was a very meaningful experience - we imagine some kind of divine blessing at these moments.

Great artists tune-in to some fundamental principle of the universe. They often struggle to articulate exactly what that is, but it is clearly evident in their work. Academics are often arrogant enough to believe that they can unpick these fundamental principles - and make themselves look foolish in the process. In between the artistic expression and the academic "sense-making" is a process of loss of information. This is more pronounced in academic work which is "easier" to digest in the academy - that which divides things up into structural and formal relations, or carves it up on a spreadsheet. Its like how dissecting a frog destroys the living essence of frogness.

So if we have to academicise great art, there should be something as impenetrable in our scholarship as there is in the art. For me, the best theoretical work is like this, where theory has a similar structure to the thing it theorises. We tend not to think like this. We look to theory to "explain", where it can be something that accompanies us on a journey. It is a bit like how I described Gordon Pask's thinking about information the other day: not as a calculation, but a physical process. 

Music is a physical process. It is a process of physiological adaptation to perturbation driven by nature's tendency towards homeostasis. What drives that process we don't know, although there are emerging theories as to how it might happen. Much more difficult is to think how we might measure a process, or even to think what measurement actually means. 

Today we are used to using computers to measure things - often with statistical formulae. But what is a computer? What is a machine? So, here is Gordon Pask again on that with a statement I find very profound:

"The word 'machine' means a piece of hardware constrained, algebraically, to act as a computer"