Educational Metatechnology and Indifferent Data

Data, whether big, small or indifferent, is really all about counting. Typically, 'big data' involves the counting of words. I rather like the idea of 'indifferent data': how would you count that? Being indifferent, there's not much remarkable, or countworthy, in it one would think. But what makes 'big data' so countable? What, in fact are we counting?

There are two things to clarify here. If you've only heard of 'big data' as the new scientific buzz-word, but not thought about exactly what it is, then my statement that it is simply about "counting" might strike you as a crude oversimplification. But it's not: most techniques of data analysis rely on probabilitistic (hmmm - that's problematic!) theories of Shannon or Bayes, each of which relies on counting like-events and distinguishing them from unlike-events. Yet by counting words in big data - facebook posts, tweets, blogs and so on, we can indeed create remarkable inferences: Google translate does a pretty good job of converting one language to another by simply counting words! But the success of Google translate raises more questions: what is it that happens when we 'count' anything?

David Hume puzzled over this over two hundred and fifty years ago. His question was how scientific knowledge was possible; our question now is something like "how is big data analysis scientific"? Yeats says "measurement began our might" no doubt partly thinking of Blake's foolish Urizen (who Blake saw as a demonic Newton) using his divider to map the heavens, but also acknowledging that some balance had to be struck between Bacon, Newton, Locke and the poets. Hume is perhaps the figure whose scepticism is well-placed to create Yeats's balance. He saw that counting required the identification of analogies: that a 1 by virtue of its similarity to another 1, together make 2, and upon the induction that other 1s will also be analogous, knowledge is founded. Yet, Hume asks, upon what grounds is this similarity determined? The question is more pressing when we try and count words. How many times do I say 'words' in this document? Is each use of the word 'words' an equivalence? Does it mean that each time I mean the same thing? Might I not be like Humpty Dumpty in Alice through the Looking Glass and say that when I use a word, it means whatever I want it to mean?! And what if I look for the word "word", rather than the word "words"? What then?

Counting is the determination and aggregation of analogies, and of surprises - or anomalies. Analogies are not determinable without the determination of anomalies. Fundamentally there is a distinction. More fundamentally, these distinctions have to be agreed - at least between scientists. Since Hume's scientific epistemology was all about the agreement between scientists about causes, the agreement about analogies is a pretty central part of that. Actually, Hume wasn't entirely clear on this. It took a 20th century genius to dig into this problem, as he grappled with the madness of mathematical abstractions in economics. John Maynard Keynes's "Treatise on Probability" of 1921 is his masterwork (not so much the General Theory, which owes so much to it). The Keynesian twist is to see that the business of 'analogising' in order to count is a continual process of breaking down things that we initially see to be 'the same' (in other words, things that we are indifferent to) and gradually determining new surprises (anomalies) and new analogies.

The point is that the agreement of analogies and anomalies is a conversation between scientists. Without actual embodied participation in the phenomena which produce the analogies and anomalies, there is no way of coordinating the conversation. Without any way of coordinating the conversation, there is an encroaching mysticism: nonsense explanatory principles take over - the 21st century equivalent of phlogiston, or the 'dormitive principle of ether' in Moliere. Data becomes a religion divorced from science. Education driven by data in this way is also divorced from science. We end up in the worst-case scenario: an educational system renouncing the humanities and arts because they are unscientific, whilst embracing a science which is in the thrall of quackish data analysis!

Can data restore the scientific balance? Can we answer the question "how is big data analysis scientific"? The trick, I believe is to see the identification and counting of analogies and anomalies as the identification of constraints - the identification of what is not there. The problem with Western science is that it has become over-focused on causation, or presence and actuality. Education is a domain which shows that causation is clearly a nonsense concept: so much idiocy has been devoted to the 'causes of learning' - including the forthcoming Teaching Excellence Framework. (There's no point in fighting the TEF: it will happen, it will fail - and maybe then people will think harder). But science really is about constraint, because all living and non-living things realise the possibilities of their existence within constraints. In education, 'realising the possibilities of existence' is something we call "learning". Teachers manipulate the constraints - if they are themselves free enough of constraints to do the job properly.

We can count words in documents and in doing so we can learn something about the constraints we are operating within. In this blog post, English grammar constrains me as much as the meaning I am trying to convey. We can agree the analogies of our counting. We can critique the analogies of our counting, and seek new analogies and anomalies to focus on. Each step of the way we discover more about the conditions within which we live and the ways those conditions are reproduced and transformed by us. We can, of course, do much more than count words in documents: there are analogies to be found everywhere; new defensible "countings" to be performed. At each level, we see what is not. We will see how warped our education system has become, how its ecology is under threat, how the collapse of university education into apparently 'successful' businesses threatens civil society, how the market in education works like CFCs on the ozone of our social fabric. This is the beginning of an educational metatechnology.

So measurement did "begin our might". But the language of poets and musicians can also be counted in ways which show how an aesthetic ordering of constraint - of what is not - might be coordinated for the flourishing of an ecological social fabric.

Educational Metatechnology and Listening

Our computer technologies are bad at listening. Of course, they record all the text we send to each other - to which the security services continually 'listen' to make sure we are not extremist nutters - but among the many reasons why we should object to what the security services do, the most important is the fact that their analysis of vast amounts of data is NOT listening. No doubt, some terrorist plots have been intercepted - for which some people should be grateful. But it doesn't pick up the disquiet about liberty and surveillance, increasing social alienation, atomisation and technocracy all of which feed the appetite of those who would seek to commit terrible crimes. Selective listening is not listening: more than not listening to the dynamics of social pathology, it becomes part of that pathology - selective listening is listening to fear and this is what our communication technology gives us.

It doesn't have to be GCHQ. Online education produces vast amounts of data. We analyse the data and detect that 90% of people have dropped off MOOC a, and 87% dropped MOOC b. Surmising what this tells us about the respective merits of MOOCs a and b is not an act of listening. It is the opposite of listening. MOOCs are a bit like very bad elevator music: it makes everyone feel bad, but some people manage to get to the top floor in the elevator despite this. But because we think that listening to the data of online education is listening, and because we act in response to it, we turn up the volume of the bad music, piling injury upon injury to education as we increasingly fail to listen to what's happening.

What we should really be listening to is our feelings. Technocracy and functionalism have overridden education to the point that the phenomenology and the politics of education have been squeezed out in favour of data and marketisation. A conversation is not an exchange of text whose contents can be analysed. If it were, all our conversations would involve us creating documentary evidence of our utterances and our meaning (the metadata!). We don't do this in the flow of everyday conversation. The word 'conversation' is from the latin - to "turn together" (con-versare). Turning together through the exchange of text documents is a somewhat stilted affair. In most online conversations, we dance alone with imaginary partners, only to correct our moves in the light of text signals from other people. But it is hit-and-miss.

It is the job of universities to listen. They now fail to listen because they have become constrained by technocracy, technology and markets. As they fail to listen, they will hurt people. The emotional damage they risk creating is not just to the staff they sack in their effort to be efficient, or the brilliant minds they never employ (most of my favourite academics would not get jobs in Universities today), but the damage to their students, alienated by increasingly rigid curricula, failed through unrealistic promises about "graduate premiums", burdened by debts that strike when they are beginning to establish their own families on incomes more meagre than they had hoped or were promised. Behind all of this are feelings of betrayal, anger and confusion.

Emotions really count. All good teachers know this. Not listening to emotions is very stupid behaviour, and our universities risk becoming good at not listening, or believing they are listening when they are not (even more stupid). In the final analysis, emotions drive new movements and change the world - but in ways which are not always peaceful. Universities must listen to everything - not just their market constraints. Their job is to reimagine the world, to explore what Ron Barnett calls "feasible utopias".

We have not got our technology right. Which leads to the question as to what a proper 'listening' technology might look like. I believe that what we should be looking at is a technology which helps us to understand our constraints: a technology for the management of a "social ecology". Since today's technology has become the single most powerful constraint upon the ways each of us lives, a technology which helps understand constraints is a metatechnology. It has to be a facilitator of conversation about technology: not conversation as the exchange of text documents, but the means by which we look into each others eyes and ask what our screens are doing to us.

Christmas in Vulgaria

Zoltan Hubriski can do no wrong. His hugely successful recruitment drive bringing "his people" (nobody quite knows who 'his people' are) into the University has united more bottoms with more seats than any other recruitment initiative in the University's history. How does he do it? Was it the white-suited sales pitch or the winkle-pickers that did it? Hubriski explains it thus: "My people are like sheep. Once you get one, everyone else follows!". So there we have it! This success is skin-deep; it's actually a catastrophic failure of principle, honesty and integrity dressed-up as success. So much for success at the University of Vulgaria.

Hubriski's cynicism is only matched by the cynicism of his overlords who gaze on approvingly. "it's for the good of the learners," they tell everyone earnestly, whilst quietly saying to themselves, "it's for the good of me." Nobody believes they really care for the 'sheep': deep down everyone knows the score - even the sheep!

A full-moon at Christmas and there's a certain eeriness in the air this year. In Chateau Turtonovski, the baron's Bentley pulled-up as the wind and rain rattled the windows. The baron rarely stops to listen to anything, but this time something in the whistle of the wind caught his ear. It wasn't thoughts of Hubriski ("The man's an idiot, but for some reason he's successful!" he puzzled). He thought of the Markeyovich houshold. "What were they doing now?" asked the baron to himself, remembering how he had ruthlessly banished them from Vulgaria earlier in the year. The baron didn't want to think about this, but he couldn't stop himself. His mind tried to shake-off the thought - "I don't care for Markeyovich or his ghastly family!". But no sooner did he think he had shaken this one off, other names came to mind... the screwdriver man, banished for 'stealing a screwdriver' - ("that was a close-shave - we had to back-down because of the idiot Hubriski!" muttered the baron to himself disconsolately). Then there was his former educational research department whose intellectual critique of the damage that was being done the University by the Baron and his cronies inevitably sealed their fate ("they had to go - we engineered their departure rather well by starving them of funding!" he said with some satisfaction, as the words "knowledge" and "university" irritated his brain in a way he couldn't fathom). Then there was the dismembering of so many others: The Pro-VC ("he stuck to his principles and departed from the script!"), the academic registrar ("she asked too many questions"), the HR trouble-shooter who didn't last long ("I threw him out of the car!"), half the psychology department ("we can get better and cheaper academics!"), most of the old business school ("I wish we could get the cheaper replacements to stay..."). Among them all some wonderful souls with wonderful ideas and caring hearts. "I don't care! We need to make money! Hubriski's the man! Why couldn't they be like Hubriski?" shouted the baron defiantly at the wind and rain.

Then there was the decommissioning of various heads of department - perhaps Prof. Veritaski as head of health was the most brutal, or the dismembering of the staff-development unit ("we don't need staff development; we don't want people to stay - get 'em in, work 'em to the bone, get 'em out!"). Or there was the sudden disappearance of the newly-arrived PA to the newly-arrived prof. McSortemout who caught wind of a salacious rumour concerning an attractive member of staff and accidentally trod on a land-mine. Then there was the disproportionate number of middle-aged women who disappeared from the university: more than any other group, they bore the brunt of banishment ("hmmm - blame the baroness" the baron explained to himself, "she's a jealous woman - I'm scared of her!"). "That wonderful lady from Personnel... the one from engineering (that was the first sign things were going badly wrong)... a few from health...education..." All gone. "I don't care," he repeated to himself.

He struggled with his key in the rain. It wouldn't work. "Damn it!" he said as anger took hold. The angry wind whistled vengefully around the ornamental garden. "Angry! - that's how they all feel!" he thought to himself. "You wanted to control everything," he couldn't stop the voice of the collective ghosts of the University telling him. "You wanted a University in your image. The University of You. You didn't care for justice, knowledge or decency - you just went after what you wanted. You are a greedy and insecure man who destroys knowledge and surrounds himself with thugs. For some of us, who care for knowledge and the university, what you did has left a deep scar. Injustice really hurts, you see. We lay in a kind of purgatory for some time - some of us are still there. You thought you had done the job and we had gone away. But we're only just beginning to have the strength to get really angry". The baron pulled his coat tighter and looked over his shoulder nervously. He noticed how shallow success looks different in the dark. He managed to open the door. Behind him the ghosts began to rise from their individual, isolated torment and stand together.

Theory-Practice Gaps in Educational Technology: Why Cybernetics matters

There is a gap between the conceptual discourse about education and the practical stuff which people do with each other in teaching and learning. Conceptual theorists ask what we want from education; teachers, educational technologists and designers ask about the best ways of organising teaching and learning using the available tools and resources. Conceptual meta-theories do not often translate well into practical activity, and practical people are less concerned with thinking about the state of education. Yet both sides of this are important. There is one discipline which fits between the gaps, and that is the discipline of cybernetics.

To say “cybernetics” today is to invite some puzzled looks – “is that about robots?” (ask people who think of the “Cybermen” in Dr. Who), or perhaps people who associate it with “cyberspace” and assume it’s about the internet. In fact, it has some relation to both robots and the internet, neither of which would be possible were it not for the pioneering work of cyberneticians in the 1940s and 50s like John Von Neumann (whose computer architecture set the blueprint for every computer, mobile phone and smartwatch we use today), or Claude Shannon, whose reasoning about data transmission in networks lay the foundations for today’s computer networks, data compression algorithms, encryption, and without which there would be no internet. 

People are less likely to associate ‘cybernetics’ with psychotherapy or anthropology: and yet within these far more human disciplines, cybernetics made transformative contributions through the work of anthropologists like Gregory Bateson and Margaret Mead, and psychologist R. D. Laing, whose ‘family therapy’ (now a mainstay of psychotherapeutic services) was based in cybernetic theory, or the deep understanding of the developing child in the work on ‘attachment’ by John Bowlby. The connection of cybernetics to management and business is also unlikely, yet key thinkers from the business community have been deeply influenced by cybernetics, from Stafford Beer’s Management Cybernetics, through to George Soros’s economic reflexivity. The connection of cybernetics to biology is also unlikely to be acknowledged, even though it is through biology that the first identification of a ‘system’ was established long before the cybernetic revolution, and where biological cybernetics has inspired not only new thinking about biological development, but ecology and epistemology. Neither will people think that cybernetics has had any influence on our understanding of society, despite considerable impact of sociologist like Niklas Luhmann. Perhaps least likely will be any awareness of the importance of cybernetics in theories of learning and education. Yet learning theories from Piaget to Bruner to Mezirow adopt systemic cybernetic ideas. In education, perhaps more than in any other field, there is a deep need to connect the questions about WHY things are the way they are, HOW things operate in the way they do, with practical inquiry about WHAT IF things were done differently.

One of the more challenging responses to the mention of the word “cybernetics” is the response (possibly from those who know something about it) that it is DEAD, that it was something people talked about in the 60s and 70s, that it was utopian, control-oriented, philosophically-ungrounded – something to be treated with suspicion. Today, people talk about ‘big data’ and surveillance, economic inequality is rife, violent extremism harnesses technologies to terrorise the people, exclusive university education becomes increasingly expensive, and the ecological balance of the planet is under threat. Under these conditions it is hard to see how a subject which offers a genuine transdisciplinary approach to looking at the world's problems could be seen to be dead: except to say that the perception of its death is a symptom of the terrible mess we are in. 

Then of course, there are the other sciences which have emerged from cybernetics, and those sciences which transformed themselves in its shadow. From Artificial Intelligence to Complexity science, ecology to neuroscience, each took a small part of what existed in cybernetics that was of interest to them and developed it, in the process, losing sight of what they left behind. The whole of cybernetics is greater than the sum of these parts; indeed the existence of the parts instead of the whole thing is symptomatic of the pathologies of reductionism within the education system.

Cybernetics is a way of thinking which isn't hide-bound by disciplines. It is for this reason that cyberneticians have rarely found comfortable places in Universities. But then perhaps "comfortable" places in universities are not the places to be in universities in the first place! Cybernetics belongs in the awkward places between things - and it is possibly for this reason that a number of cyberneticians have taken an interest in educational technology. 

Visualising Constraint in Educational Institutions with Parallel Coordinates

I'm preparing a presentation for the SRHE conference later this week about status functions and constraints in institutions. Status functions are Searle's idea for how social reality is manifested through particular kinds of declarative speech act - i.e. "This is a University/certificate/banknote...etc". The argument of the paper is that they can be analysed by looking at institutional strategies (these are, in the end, collections of status functions), technologies, league tables and so on, and each of these status functions has a constraining effect on institutional life. Moreover, status function declarations exist in webs where there are many inconsistencies, contradictions and often 'knots' where competing status functions constrain each other to create a kind of stability. I think Searle is not quite right in saying that social reality results from status function declarations; but it seems reasonable to argue that social reality is certainly constrained by status functions. Maybe things like Universities, monarchies, nation states and e-portfolio(!) only exist because of the knotted constraints they tie in each of us...

Analysing institutional strategies is one way of indicating status functions, but Searle also says that status functions have to be upheld by the 'collective intentionality' of the community for which they are intended. Deep down, we agree that David Cameron is Prime Minister, and a £10 note is worth £10. We're probably less clear about education, but the knotted constraints of education including the value of certification and social and cultural capital for employability leads people to go to extraordinary lengths to ensure that their children get "the best" education, and leads young people to ask few questions about heavily indebting themselves for a degree. And that's before we consider the status functions of education itself: learning outcomes, assessments, curricula, timetables, lectures, VLEs, e-portfolios, academic papers, textbooks, and so on. We all buy into the whole thing and tend to ask few questions about something which would seem quite perverse to a Martian visitor!

Whilst the status functions of strategies and league tables are there to be seen, seeing the 'collective intentionality' requires that we ask people about it. The paper reports on some work I did with colleagues at the Far Eastern Federal University (FEFU) in Vladivostok. For Russian universities, the status functions of league tables and prestigious journals are particularly constraining because they are all in English, and dominated by a Western European/Anglo-Saxon academic culture. Russian academic traditions are different, yet the status functions are made by Western publishers like the Times Higher Educational Supplement. The Russians have to buy into it, but it's hardly a level playing field (the same argument applies to non-research universities in the UK, of course).

The problem is that things like the QS rankings constrain the strategic decision-making within institutions, where managers feel that their institution should be doing all it can to raise its league table position. This can put teachers in an impossible position.

So at FEFU we asked teachers to rank the constraints they felt prevented them from enhancing research and teaching. We then asked them to consider those things which constrained them least, and asked them what they might do to overcome the least constraining things. The data we got back was quite messy, but a visual analytic approach helped to identify some patterns.

Parallel coordinates, pioneered by Alfred Inselberg (who has a cybernetics background), is a powerful technique for doing multivariate analysis in a visual way. I've used the javascript library D3 which does a nice job of making interactive parallel coordinate graphs. There are no surprises about the consensus as to what is most constraining with regard to research: the second bar along in the graph above represents "too much teaching" and the 9th represents "bureaucracy". But the strong constraints are possibly less interesting than the weak ones. The only problem with "weak constraints" is that people don't really see them as constraints; rather they might perceive a 'weak constraint' as 'irrelevant'. Quite a few teachers felt that the abilities of their students wasn't a great constraint on their research activities (indeed, I suspect they may have seen it to be an irrelevant factor). In answer to the question "What can you do to address the least significant constraint?" some responded by emphasising the possibilities of doing more interesting things in class and enthusing their students: this at least was within reach for teachers - although it doesn't seem to fit with the constraint of feeling that there was too much teaching!

What I find interesting at a broader level about this is that the graphs provide a kind of model of the collective intentionality of the staff, and that with this knowledge, institutional policies which work with, rather than work against, the prevailing collective intentionality are more likely to be successful. More importantly, modest strategies for more inventive teaching (say) or freeing up the curriculum could change the institutional constraints to the point that ways of raising the international reputation of the university can reveal themselves without directly tackling things like the QS rankings. 

Oblique strategies and effective realistic analysis of where the land lies may be far more successful in the long term. What is important is to have analytical techniques which can pinpoint areas where strategic status functions in the form of new initiatives might be created which are likely to be upheld in a constructive way by the majority of teachers.

Educational Technology and the Intersubjectivity of the Anatomical Theatre

I started a new job working in a faculty of health (*but now I can't say where*). I think health is a fascinating and important domain for educational technology. It was the domain which largely drove initial developments in e-portfolio, competency management and simulation, as well as being an important test-ground for pedagogies like PBL (although this has interestingly fallen out-of-favour). In my interview I commented that one of the things that really fascinates me in health is that it has become apparent over the years that "competencies are not enough"; or rather that the bureaucratisation of box-ticking and form-signing has tended to instrumentalise the educational process, leaving much of the important learning beyond assessment schemes (although no doubt it influences outcomes). Maybe that's as it should be, but it does seem that instrumental education is not great either for teachers or learners.

All this made think about how medical education has happened over the centuries. One of the most fascinating educational technologies' in health education is the 'anatomical theatre'. This designed room where students would gather round on steeply banked platforms usually in a circle, where at the centre would be a surgeon demonstrator and a cadaver.

What was going on in this space? What happened in the minds of the students? First and foremost, it was theatre, so perhaps the question is one that relates to questions about what happens to us when we watch a play or television. Except that the groups of students would have been more involved in the action. It would have been hot, intense, probably smelly - there would have been a complex relationship between the demonstrator surgeon and the students and between the students and each other. Each student could look across at each others' reaction. The demonstrator would occasionally look up at the students staring down.

What was going on here is what Alfred Schutz calls 'tuning in' to the inner life of each other. Schutz emphasises the shared experience of time in these kind of intense situations.  Within these 'tuning in' engagements, knowledge would have emerged about the nature of causes and effects within human anatomy: "if I do this, this happens". But it was more than the information about cause and effect; it was the sharing of the experience of activating a cause and experiencing its effect - not just on the body, but on everybody watching.

Coming back to the instrumentalisation of education, the business of theatre and the construction of knowledge about causes and effects has largely been replaced by the simple didacticism of cause and effect. Cause and effect has been stripped of its intersubjective context. And the logical development of this is competency divorced from its social practice and context.

My point in saying this is that there's an opportunity to address this. If we could think back in history and understand the intersubjective relations of the anatomical theatre then we would design our educational technology, and our assessment frameworks differently.  Our current learning technologies make assumptions about knowledge which sit on shaky foundations and which our ancestors possibly had a better grasp of than we do. A bit of history might go a long way in rethinking our current educational practices!

Re-understanding "Understanding Computers and Cognition"

I will always regret nobody told me about Winograd and Flores's "Understanding computers and cognition" when I was a teenager first encountering computers. As it was, I read it at the recommendation of Oleg Liber in 2002, and it transformed my perspective of not only technology, but art, education, emotion and meaning. It provided a framework for a deeper understanding of technology and its relation to human organisation which is so fundamental to the exploitation of computers in education. I am so grateful for this, although in the years that have passed, through numerous projects involving technology and education, my enthusiasm for the cybernetic theory and the phenomenological and analytical philosophy (Heidegger and Speech act theory) that underpinned Winograd and Flores has waxed and waned. But now we live in age when our teenagers cannot remember a world without the internet, it is a book that demands study even more urgently.

Winograd and Flores's (really, it's Flores's book) real achievement is that they asserted that computers were about communication not data processing and AI (which was the dominant view in 1986), and they were proved spectacularly right a few years later with the advent of the web. It's notoriously hard to make technological predictions: they showed the way to do it - with cybernetics and philosophy!

But that was 1986. What would they say if they were to write it now? Their theoretical ground is slow moving - but there has been movement - most notably from John Searle, whose Speech act theory they relied on most heavily, using it to construct their "conversation for action" model. In recent years, Searle has thought very deeply about "social reality" - something which his younger self would have dismissed as an epiphenomenon of speech acts. His recent work remains language-based, but he acknowledges the existence of social institutions, presidents, money and armed forces as something more than an individual construction. Social reality is constituted by special kinds of speech act called 'status functions': declarations by powerful individuals or institutions about states of affairs, networks of rights, responsibilities, obligations and commitments, upheld by a 'collective intentionality' which plays along with the declaration. So we have 'money' (the status function declaration "I promise to pay the bearer..."), university certificates, company declarations, laws, and so on.

We also now have software, online networks, educational technologies, web services, systems interoperability, Twitter, Facebook, porn, trolls and Tinder (to name a few!) How do status functions amd collective intentionality relate to these? The complexity of these new technological forms of "social reality" make me think that Winograd and Flores's original "conversation for action" diagram now needs to be re-thought. They saw computers as ways of managing social commitments we make to each other (commitment has been a key feature of Flores's work).. But commitments are situated within a web of status function declarations which make up the social world. The speech acts that people make in agreeing or disagreeing to do something are much more nuanced than Winograd and Flores originally thought. Technologies now come with layers of commitments: to agree to use system x is to get sucked into a range of new status functions which aren't immediately visible on the surface. Teachers might initially think e-portfolio is a good idea; but after experience with the e-portfolio system, they find the commitments to the various sub-status functions of the system conflict with other aspects of their practice, and so they find themselves either not doing what they originally committed to do, or having to rethink fundamental parts of their practice which they might not have reckoned with at the outset. This can help to explain why thousands of people sign-up for MOOCs, but so few complete them.

As our technology becomes more complex and our institutions become more technocratic, the accretions of layers of status functions within the technology demands an ever-shifting compliance. The problem is that critical engagement with the technology - where we seek appropriate technical solutions to real social problems - can lose out to slavish human adaptation to the technical machinery with the consequent loss of responsibility-taking and autonomy: we let the technology create problems it can solve. The result is a conflicted self, torn between human needs and technical requirements. The later Heidegger (which Winograd and Flores ignore, concentrating on his earlier work) had a rather bleak name for this: "enframing".