Humanist Discussion Group, Vol. 36, No. 33.
Department of Digital Humanities, University of Cologne
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Date: 2022-05-26 14:19:50+00:00
From: Fishwick, Paul <Paul.Fishwick@utdallas.edu>
Subject: Re: [Humanist] 36.32: in the dark
Dear WIllard
We are in the dark with computers since none of us will take the time to
understand the program at a very fine grained level: e.g. machine code.
So, we must make do with models. The highest level models are what the
psychologists term "mental models." We each make mental models so
that we may use technology. This gets back to the McLuhanesque "we
use machines and machines use us". They "use us" by forcing us to make
mental models (even to use something simple like a toaster).
The advent of deep learning takes this to a new realm since the mental
model reflects the overall architecture of the neural network and we need
to maintain a vision of optimization rather than a more understandable
set of rules.
-paul
Paul Fishwick, PhD
Distinguished University Chair of Arts, Technology, and Emerging Communication
Professor of Computer Science
Director, Creative Automata Laboratory
The University of Texas at Dallas
Arts & Technology
800 West Campbell Road, AT10
Richardson, TX 75080-3021
Home: utdallas.edu/atec/fishwick
Media: medium.com/@metaphorz
Modeling: digest.sigsim.org
Twitter: @PaulFishwick
ONLINE: Webex,Collaborate, TEAMS, Zoom, Skype, Hangout
On 5/26/22, 1:16 AM, "Humanist" <humanist@dhhumanist.org> wrote:
Humanist Discussion Group, Vol. 36, No. 32.
Department of Digital Humanities, University of Cologne
Hosted by DH-Cologne
Submit to: humanist@dhhumanist.org
Date: 2022-05-26 06:01:05+00:00
From: Willard McCarty <willard.mccarty@mccarty.org.uk>
Subject: in the dark
A philosopher of science I know has complained that there are good
grounds for questioning the veracity of many papers he reads. The
problem is, he says, that they often are more concerned with justifying
their conclusions than re-enacting the routes taken to reach them. Even
when the intent is clearly to report on the steps taken, in a rhetoric-free
"writing degree zero" (Barthes), the complex processes involved are
simplified, setbacks left out, confusions and controversies passed over
and so on. My former colleague at Toronto, Russ Wooldridge, liked to
point out that in much published research in the humanities which used
computing, the computer quickly disappeared into the background
once useful results were obtained, thus obscuring the means, the
setbacks, the controversial moves -- and perhaps more interesting
results (positive or negative) than those reported.
In research involving a computer, is not the problem worse in
principle than in other experimental work? One has the data,
of course, and the software, and knowledge of how the machine
works--but (I hear the objections quickly forming) the machine is
largely a black box.
Let me use an analogy. If you're old enough to remember chemical
photography, you may recall the photographer's developing bag, black
inside and absolutely light-proof, with elasticated holes for the arms
so that film and developing apparatus could be manipulated without
exposure to light when a darkroom was not handy. One got quite good
'seeing' with one's hands. (Those with impared vision get to be very good
at navigating the world without visual help, of course. They are the
experts here.)
Are we not REALLY in the dark with computers -- and so necessarily
writing close to "degree zero"? So much for 'objectivity', the less so the
greater the amount of data, the closer to complexity the process gets?
Comments?
Yours,
WM
--
Willard McCarty,
Professor emeritus, King's College London;
Editor, Interdisciplinary Science Reviews; Humanist
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