No Subject

Fortunately a couple of days after the Lux show, I met up with Dr
Debra Tafnus, a rabid mathematician from the Institute of
Post-Predictive Computing.  I decided that she and the IPPC had
something crucial to add to the debate. This is the result of an
interview that I conducted with her over coffee in the cafe at the
Tate Modern.

As we began, Debra stared out over the financial district of London
and the St Paul's Dome, muttering and shaking her head:

DDT: Money, mechanisation and algebra: the three monsters of
contemporary civilisation. Money, mechanisation  and algebra: the
three activities identified as the prequisites of the computer. Those
of us who love mathematics and revere it as one of the great
expressions of our humanity like my dad did, will want to ask why it
is thought that mathematics, in cahoots with its other two
accomplices, has given rise to such statistical monstrosities. My dad
once had a dream of social salvation through a technological utopia.
Now his dream is gone, all gone.

H: Debra, I know you have strong feelings about the procedural
corruption going on in the application of mathematics and
computerisation at the moment. But do you think that web art has a
sufficient critical understanding of the agenda behind the
mathematical models it uses?

DDT: No. You people dance around the edges of subjects, making
yourselves look good by making the next in-joke, like Matthew Fullers
'A song for occupations', or camping up outmoded technologies with
some old windows music programme.

H: What gives current mathematical models their power?

DDT: A computer model can be stopped at any particular procedural
phase and assessed to give a reasonably reliable premonition of
impending doom or predict the normative growth of our toenails. Look
at this simple model of bacterial growth, one that is hopefully
familiar to any of the biotech terriers in your avant-garde (she
writes the mathematical generation model of bacteria growth on the
back of a napkin with her eyeliner pencil):

Generation time - ( 3.3 log ( b0 / b1 )) / t

where t - the time interval between the measurement of cell numbers
at the point in the log phase(b0) and then again at the later point
in time (b1)

b0 - initial bacterial population
b1 - bacterial population after time t
log - logarithms to base 10
3.3 - log 10 to log 2 conversion factor