Hi Matthew,
Congratulations! A great issue, a really timely and urgent extension of
the line of thinking that I encountered first in Joque's book. The use
of Bayesian statistics might create an opening towards very different
political ends than those which is is currently used for and that
exploring this opening might be a more productive than simply "resisting
(AI)". We talked a bit about that over dinner recently.
In much of the philosophy/epistemology concerning Bayesian statistics
the issue of the "prior" is absolutely central, and your intention to
turn of it from a problem for objectivity into the foundation for
situatedness is absolutely correct.
What is usually less discussed, perhaps because the issue not unique to
Bayesianism, is the question of the threshold. When is the likelihood of
an hypothesis being true strong enough to act as if it were true?
In ML, they try, as you write, minimize the situatedness by using
"noninformative priors" despite the extra compute this requires, but
they can at least to be non-subjective. In many ways, the prior is
subjective only in a context where computation is scare. In a context
where computation is treated as abundant, it's meaningless, a random
starting point in a very long line of iterations. It's not subjective,
but brute force ;)
But the situatedness creeps back in through the threshold. What degree
of error is acceptable, which is always also a question of who has to
cover the costs of these errors. In this way, Bayesianism create a new
type of externality.
I think this question of threshold, while not unique, is particularly
urgent in Bayesian systems because they are less about generating
knowledge (in a conventional scientific way, there the threshold is a
stable p-value) than about enabling agency, on the spot, under a
subjective risk/rewards ratio. In certain systems, say placement of
advertisement, a 20% likelihood might be sufficient, in others, say,
systems in HR departments, one would hope of a much higher threshold.
The point being, the threshold is entirely subjective.
The consideration of the subjective/situated/political nature of
threshold might open up less towards the issues you are concerned here,
but more towards social justice question (how to distribute
risks/rewards), but as a source of subjectivity it's a bit underrated.
Anyway, great issue!
all the best. Felix
On 7/25/25 09:28, Matthew Fuller via nettime-l wrote:
Computational Culture, a journal of software studies
Issue Ten, July 2025
Special Issue: Situated Bayes
Edited by Juni Schindler, Goda Klumbytė and Matthew Fuller
Special Issue Introduction
Juni Schindler, Goda Klumbytė, Matthew Fuller, [Situated Bayes – Feminist and
pluriversal perspectives on Bayesian
knowledge](http://computationalculture.net/situated-bayes/)
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