[Humanist] 28.51 when the model becomes the sole object of study

Humanist Discussion Group willard.mccarty at mccarty.org.uk
Fri May 23 22:10:08 CEST 2014

                  Humanist Discussion Group, Vol. 28, No. 51.
            Department of Digital Humanities, King's College London
                Submit to: humanist at lists.digitalhumanities.org

        Date: Fri, 23 May 2014 16:10:39 +1000
        From: Willard McCarty <willard.mccarty at mccarty.org.uk>
        Subject: model and reality

In "Models of and Models for: Theory and Practice in Contemporary 
Biology", Philosophy of Science 67 Supplement (2000): S72-S86, Evelyn 
Fox Keller describes modelling work toward what the scientists concerned 
call a "genetic computer". (Those keenly interested will want to look at 
Chiou-Hwa Yuh, Hamid Bolouri and Eric H. Davidson, "Genomic 
Cis-Regulatory Logic", Science NS 279.5358 (1998): 1896-1902), esp their 
Figure 6.) Keller goes on to ask, "How literally are we to take the 
metaphor of a 'genetic computer'?" I think not a few here will find her 
response worth pondering:

> Computer metaphors have been commonplace in biology for almost half a
> century. But until recently, they have been just that, i.e.,
> metaphors, carrying no expectation of approaching literal
> correspondence. Computers may have been seen as functional analogues
> of biological systems, but not as structural analogues: no-one would
> have taken them as even approximately corresponding to the physical
> structures of DNA, cells, or organisms. This was a metaphor,
> therefore, without hope of approximating literal truth. That is, not
> until the last few years, when a number of computer scientists began
> to look to molecular biology for new horizons in computer technology.
> Today, as some researchers in computer science seek to harness DNA
> for conventional computational purposes, and as others have gone into
> the laboratory to build into real bacteria specific gene regulation
> networks (sometimes referred to as "gene chips") that have been
> pre-designed to respond to particular stimuli, the gap between
> computers and cells has narrowed dramatically. The net result is
> that the ''genetic computer" is no longer just a metaphor or even
> just a model: in two quite different domains, on the one hand, in the
> designing of new kinds of computers and on the other, of new kinds of
> organisms, the 'genetic computer' has begun to acquire something
> resembling literal truth. However, the route by which this
> convergence has occurred bears little resemblance to the story
> usually told about scientific metaphor. Here, the convergence is
> simultaneously material and conceptual, and there is no residually
> literal sense in which any of the referents remain fixed.
> Furthermore, it is possible to track the large and conspicuously
> instrumental role played by the metaphor itself in bringing its
> referents together-not only in the immediately conceptual sense of
> directing the attention and perception of the researchers, but also,
> and in rapid suit, in the sense of guiding their material
> manipulations in a number of different kinds of laboratories
> (biological, computational, and industrial), and to a number of
> different kinds of ends (development of theory, of laboratory
> instruments, and of commercial products).

The model and the modelled converge. Keller concludes that "for many 
workers in [molecular biology] today, 'use value' has now come to be 
taken as the goal (and perhaps even the test) of an explanation: an 
explanation is expected to provide a recipe for construction; at the 
very least, it should provide us with effective means of intervening." 
She goes on:

> Where causes are understood as handles, causal propositions will
> inevitably be as much about means and ends as they will be about
> truth. And means and ends are specific, local, and interested:
> 'Means' means access, and as such, depends on the availability of
> particular resources (technical, professional, and monetary) for
> particular kinds of manipulation; 'ends' are the long-term goals to
> which these manipulations are directed, and as such, depend on needs
> and desires, be they for "understanding," for better theories or
> instruments, or for newer and more profitable commercial products.

Thus "the importance of asking how the goals of science, and the 
criteria of success by which a theory or research program is judged, 
shape the theoretical content of that science".

What we want to find out, what we find out: not because the tools are 
"scientific" but because nothing at play is fixed?



Willard McCarty (www.mccarty.org.uk/), Professor, Department of Digital
Humanities, King's College London, and Research Group in Digital
Humanities, University of Western Sydney

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