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What
can one say about the recent American election? My impression
is that a corrupt political party tried to steal a victory it
hadn't earned for a candidate who wasn't fit to be dogcatcher,
let alone hold arguably the most powerful political office in
the world. However, since my writing for *spark is primarily about
technology, not politics, I won't say this.
Instead,
one aspect of the fiasco in Florida intrigues me: the debate over
the quality of results of hand-sorted versus machine-read ballots.
Owing to a large number of rejected ballots, representatives of
presidential candidate Al Gore asked for recounts of ballots in
three Florida counties by hand. Representatives of candidate George
W. Bush responded that machine-read results were more accurate;
that when human beings were involved, bias and error would skew
the results.
I could
point out that the Bush camp came late to this party: as Governor
of Texas, Bush enacted a law which allowed hand counting of electoral
ballots. His opposition to hand-counting ballots in Florida--to
the point where his representatives argued in court that hand counts
were open to fraud--could be seen as opportunistic and hypocritical.
But, again, since I'm a tech writer, I won't point this out.
The
question this raises which is appropriate for a technology writer
to consider is: What are the relative merits of machines and people
for various tasks?
The
assumption behind the Bush camp's rejection of hand counting is
that machines are infallible and incorruptible. Neither of these
positions is entirely true. Suppose you're a voter in a Florida
booth. You begin to punch a hole on the ballot form, then realize
it doesn't represent the candidate you want to vote for, so you
fully punch the hole next to your candidate's name.
Now,
you and I would clearly be able to see the voter's intention. A
machine, however, may well see the partially punched hole as a second
attempted vote and declare the ballot spoiled. In this (and many
other ways) error can creep into the behaviours of the most carefully
designed machines.
As for
machines not being corruptible, the past 20 or so years of research
into the working of science (e.g., Latour) and the development of
technology (e.g., the technological constructivist studies of Pinch
and Bijker) clearly shows that the design of machines is never value
neutral: Machines have biases built into them in the assumptions
of their designers. The values of the creators of technology can
easily corrupt its use, as when the promise of unlimited nuclear
energy turns into the nightmare of nuclear war.
Perhaps
another example--a more important example--may help us explore the
difference between machine and human actions. One of the more successful
areas of artificial intelligence research has been in the creation
of "expert systems." With these, a large number of experts on a
given subject are interviewed; the rules of thumb by which they
function are distilled and codified into a set of rules which can
be applied by a computer.
One
area in which expert systems have been applied is medicine. One
of the things a doctor's routine includes is listening to a patient's
symptoms and choosing a diagnosis from among the many possible illnesses
the patient may have. Well-programmed expert systems can make the
diagnostic procedure much simpler.
However,
the ultimate decision about a diagnosis always rests with the human
doctor. There is a practical reason for this: The legal liability
for the mistakes of computers which are allowed to make diagnoses
has not been determined. There is a more basic reason, though.
We don't
trust computers to make important decisions about our lives. While
there may be an irrational component to this belief, it is, for
the most part, based on a very real difference between machines
and people: Machines follow rules, human beings exercise judgment.
There
are human factors in a medical diagnosis which only a human being
can appreciate. This may be a simple matter of knowing the environment
in which a patient lives, which can be a factor in illness which
doesn't show up in a simple list of symptoms. It may be as complex
as interpreting a hysterical patient's description of his or her
symptoms. Rules-based computing makes sorting through lists of symptoms
and diagnoses quick and easy; dealing with the messiness of human
existence requires human judgment.
Judgment
is the ability to make decisions in situations where the rules are
fuzzy, or simply do not apply. It also includes a set of rules over
and above those that can be programmable (for instance, when to
apply information outside of the rules). Ultimately, it takes in
all of the human experience which doctors apply to their work, and
knowing when to apply it. With expert systems (the cutting edge
of current artificial intelligence research, since they actually
have worked in limited capacities), this is simply not possible.
In the
case of the election, the voting machines used a very simple set
of rules to determine how ballots were filled out. Imagine how much
human reality was missing.
I like
computers. I work with computers. I play with computers. But, for
anything important, I trust human beings.
Copyright
© 2000 Ira Nayman. All Rights Reserved.
Ira Nayman has a Ph.D. in communications from McGill University.
He knows it's only a matter of time before his friends and family
get over it. His current email address is: ira@bydesign-elab.net.
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