Tuesday 31 October 2023

Iconicity and Epidemiology: Lessons for AI and Education

The essence of cybernetics is iconicity. It is partly, but not only, about thinking pictorially. More deeply it is about playing with representations which open up a dance between mind and nature. This is distinct from approaches to thought which are essentially "symbolic". Mathematics is the obvious example, but actually, most of the concepts one learns in school are symbols that stand in relation to one another, and whose relation to the world outside has to be "learnt". This process can be difficult because the symbols themselves are shrouded in obscure rules which are often unclear and sometimes contradictory.

Iconic approaches make the symbols as simple as possible: a distinction, a game, a process - onto which we are invited to project our experience of a particular subject or problem. It was something that was first considered by C.S. Peirce who developed his own approaches to iconic logic (see this for example: Peirce.pdf (uic.edu)). Cybernetics followed in Peirce's footsteps, and the iconicity of its diagrams and technical creativity makes its subject matter transdisciplinary. It also makes cybernetics a difficult thing for education to deal with, because education organises itself around subjects and their symbols, not icons and games. 

But thinking iconically changes things.

I am currently teaching epidemiology which has been quite fun. But I'm struck by how the symbols of epidemiology - not just the equations, but the classifications of study types, problematisation of things like bias and confounding, etc, all put barriers in the way of understanding something that is basically about counting. So I have been thinking about ways of doing this more iconically.

To do this is to invite people into the dance between mind and nature, and to do that, we need new kinds of invitations. I'm grateful to Lou Kauffman who recommended Lancelot Hogben's famous "Mathematics for the Million" as a starting point. 

Hogben's book teaches the context and history of mathematical inquiry first, and then delves into the specifics of its symbolism. That is a good approach, and one that needs updating for today (I don't know of anything quite like it). Having said that, there are some great online tools to do iconic things: The "Seeing theory" project from Brown university is wonderful (and open source): https://seeing-theory.brown.edu/  (again, thanks to Lou for that)

Then of course, we have games and simulations - and now we have AI. Here's a combination of those things I've been playing with inspired by Mary Flannagan's "Grow a Game" Grow a Game - Mary Flanagan

My AI version

Basically enter a topic, select a game and chatGPT will produce prompts suggesting rule changes to the game to reflect the topic. Of course, whatever the AI comes up with can be tweaked by humans - but its a powerful way of stimulating new ideas and thought in epidemiology. 

There's more to do here.

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