Humanist Discussion Group, Vol. 36, No. 32.
        Department of Digital Humanities, University of Cologne
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        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
www.mccarty.org.uk


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