Tuesday, 7 May 2019

"Tensoring" Education: Machine Learning, Metasystem and Tension

I've been thinking a lot about Buckminster-Fuller recently, after I gave a talk to architecture students about methods in research (why does research need a method?). One of the students is doing an interesting research project on whether tall buildings can be created in hot environments which don't require artificial cooling systems. The tall building is a particular facet of modern society which is overtly unsustainable: we seem only to be able to build these monoliths and make them work by pumping a huge amount of technology into their management systems. Inevitably, the technology will break down, or become too expensive to run or maintain. One way of looking at this is to see the tall building as a "system", which makes its distinction between itself and its environment, but whose distinction raises a whole load of undecidable questions. Technologies make up the "metasystem" - the thing that mops up the uncertainty of the building and keeps the basic distinction it made intact.  Overbearing metasystems are the harbinger of doom - whether they are in a passenger plan (the Boeing 737 Max story is precisely a story about multiple levels of overbearing metasystems), in society (universal credit, surveillance), or in an institution (bureaucracy).

Buckminster Fuller made the distinction between "compression" and "tension" in architecture. We usually think of building in terms of compression: that means "stuff" - compressed piles of bricks on the land. His insight was that tension appeared to be the operative principle of the universe - it is the tension of gravity, for example, that keeps planets in their orbit. Fuller's approach to design was one of interacting and overlapping constraints. This is, of course, very cybernetic, and the geodesic dome was an inspiration to many cyberneticians - most notably, Stafford Beer, who devised a conversational framework around Fuller's geometical ideas called "syntegrity".

In education too, we tend to think of compressed "stuff": first there are the buildings of education - lecture halls, libraries, labs and so on. Today our "stuff"-focused lens is falling on virtual things - digital "platforms" - MOOCs, data harvesting, and so on, as well as the corporate behemoths like Facebook and Twitter. But it's still stuff. The biggest "stuff" of all in education is the curriculum - the "mass" of knowledge that is somehow (and nobody knows exactly how) transferred from one generation to the next. Fuller (and Beer) would point out that this focus on "stuff" misses the role of "tension" in our intergenerational conversation system.

Tension lies in conversation. Designing education around conversation is very different from designing it around stuff. Conversation is the closest analogue to gravity: it is the "force" which keeps us bound to one another. As anyone who's been in a relationship breakdown knows - as soon as the conversation stops, things fall apart, expectations are no longer coordinated, and the elements that were once held in a dynamic balance, go off in their different directions. Of course, often this is necessary - it is part of learning. But the point is that there is a dynamic: one conversation breaks and another begins. The whole of society maintains its coherence. But our understanding of how this works is very limited.

Beer's approach was to make interventions in the "metasystems" of individuals. He understood that the barriers to conversation lay in the "technologies" and "categories" which each of us has built up within us as a way of dealing with the world. Using Buckminster Fuller's ideas, he devised a way of disrupting the metasystem, and in the process, open up individuals to their raw uncertainty. This then necessitated conversation as individuals had to find a new way to balance their inner uncertainty with the uncertainty of their environment.

The design aspect of tensored education focuses on the metasystem. Technology is very powerful in providing a context for people to talk to each other. However, there is another aspect of "tensoring" which is becoming increasingly important in technology: machine learning. Machine learning's importance lies in the fact that it is a tensored technology: it is the product of multiple constraints - much like Buckminster-Fuller's geodesic dome. The human intelligence that machine learning feeds on is itself "tensored" - our thoughts are, to varying extents - ordered. Expert knowledge is more ordered in its tensored structure than that of novices. Machine learning is able to record the tensoring of expert knowledge.

When devising new ways of organising a tensored education, this tool for coordinating tension in the ordering of human understanding, and avoiding "compression" may be extremely useful.

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