Felix,
I wrestled with your opening paragraph quite a bit:
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)".
Maybe it's because I've been writing on *resisting AI*
(https://schmud.de/posts/2025-07-15-engineering-end-of-work.html)
- but I'm not quite seeing the connection between the political
outcomes of resistance and embracing the tool with a Bayesian
mindset.
I think it has something to do with the production of knowledge,
but the foundation of this knowledge is still "conservative" in
the sense that Joseph Weizenbaum described
(https://web.archive.org/web/20211002104454/http://tech.mit.edu/V105/N16/weisen.16n.html).
Can you help me understand your optimism of this approach?
/David
[email protected] writes:
Send nettime-l mailing list submissions to
[email protected]
To subscribe or unsubscribe via the World Wide Web, visit
https://lists.servus.at/mailman/listinfo/nettime-l
or, via email, send a message with subject or body 'help' to
[email protected]
You can reach the person managing the list at
[email protected]
When replying, please edit your Subject line so it is more
specific
than "Re: Contents of nettime-l digest..."
Today's Topics:
1. Re: Computational Culture issue ten. Special Issue:
Situated
Bayes (Felix Stalder)
----------------------------------------------------------------------
Message: 1
Date: Sat, 26 Jul 2025 14:53:02 +0200
From: Felix Stalder <[email protected]>
To: Matthew Fuller via nettime-l <[email protected]>
Subject: Re: <nettime> Computational Culture issue ten. Special
Issue:
Situated Bayes
Message-ID: <[email protected]>
Content-Type: text/plain; charset=UTF-8; format=flowed
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 Klumbyt? and Matthew Fuller
Special Issue Introduction
Juni Schindler, Goda Klumbyt?, Matthew Fuller, [Situated Bayes
? Feminist and pluriversal perspectives on Bayesian
knowledge](http://computationalculture.net/situated-bayes/)
--
| |||||||||||||||| http://felix.openflows.com |
| |||||||||| https://tldr.nettime.org/@festal |
| for secure communication, please use signal |
------------------------------
Subject: Digest Footer
--
w: http://schmud.de
e: [email protected]
t: @dschmudde
--
# distributed via <nettime>: no commercial use without permission
# <nettime> is a moderated mailing list for net criticism,
# collaborative text filtering and cultural politics of the nets
# more info: https://www.nettime.org
# contact: [email protected]
