Before and after science (wk 25/2025)
A workshop on meaning-making; the future of education is meaning-making; question-value, the aesthetic value of uncertainty; what happens before and after science.
Hello friends,
This week, I ran a half-day workshop in Adelaide on different types of not-knowing that aren’t risk. The group was multi-disciplinary (psychologists, educators, mathematicians, curators, designers, futurists, artists, social workers, and statisticians) and I’m told that the participants enjoyed it and found it insightful and useful.
I’ll write more on this in the next few weeks but my main takeaways are:
It takes at least an hour to effectively explain the different types of not-knowing, but the value and relevance of the construct and typology is clear and seems applicable across a wide range of disciplines,
It takes so long because “risk” and “uncertainty” have been used imprecisely and inconsistently to describe not-knowing for decades (even by people who should know better) and this obstructive underbrush has to be cleared before a new foundation for understanding can be built,
The framing of not-knowing as a generative principle is what gets people to really engage with the typology of not-knowings, and
People with different disciplinary backgrounds come up with unexpected (to me) ways to experience the different types of not-knowing, many of which can be implemented quickly and experienced in minutes (vs hours or days).
Writing
All through June I’ve been working on a project which isn’t ready for the public yet — it’s about what education and educational tools look like in a world where AI is increasingly ubiquitous. I’ve written something short about it for now. This is the tl;dr version: AI tools are increasingly accessible, cheap, and seem potentially able to produce any output a human can produce — they’ll certainly reconfigure what work looks like. I agree with this read on AI, except for one important difference: Humans can and must do what I call “meaning-making” because AI can’t do it yet. Meaning-making consists of making subjective judgments about the relative value of things. Education at all levels, but especially higher education, has largely abandoned teaching students how to make and justify subjective value judgments. To remain relevant, education must reorient around helping students learn what meaning-making is, and how to do it well.
You can read the whole thing, plus more context at the links below.
👉 The future of education is meaning-making.
👉 What makes us human for now. [context]
👉 The meaning-making lens on AI. [more context]
Elsewhere
This week I’ve been thinking about partial knowledge a lot, and going through my old files (in some cases from decades ago) to see if I could find more ways to talk about the benefits of partial knowledge.
Robert Irwin; in Lawrence Weschler, Seeing is forgetting the name of the thing one sees:
I find it very precarious for a culture only to be able to measure performance and never to be able to credit the questions themselves ... As the questions go up, the performance level goes down — and that's natural, since people don't yet know how to act on those questions, they're stumbling around in a fog — whereas when performance goes up the quality of the questions tends to go down.
Donald Francis Tovey, Essays in musical analysis, vol. 3:
Theorists are apt to vex themselves with vain efforts to remove uncertainty just where it has a high aesthetic value.
Philipp Otto Runge to Johann Wolfgang Goethe (3 July, 1806), in Goethe’s Zur Farbenlehre (1810):
There have been those who have built bridges and suspension work and other such technical things simply by eye. That is certainly possible for a time, but once a certain height has been reached and one naturally hits upon mathematical conclusions, his whole talent will be for nothing unless he works his way through the science and back into freedom.
See you next week,
VT