From: Alexander 'Sasha' Chislenko (sasha1@netcom.com)
Date: Mon Dec 14 1998 - 15:05:35 MST
I was just discussing with my friends the utility of setting up
mechanisms for electronic poll-taking, so that elected officials
- or anybody else - would have ways of finding out opinions of
various social groups and population as a whole on various
issues.
It may be useful to set up a service where one could offer any
question for an opinion poll, suggest possible answers, and
receive statistics that can be broken down by various social
factors, as well as free-form comments. The service could also
have mechanisms for identification of respondents and verification
of their profiles.
One problem with such a system, as well as existing electronic
polls, is that they are "not representative" - that is, while
reflecting the opinions of people who are taking the poll, the
statistics do not necessarily reflect the average opinion of
the population. (One may doubt though that diluting the opinions
of active people who understand the Web with those of people
who don't care about the issues enough, or can't figure out
how to click on buttons, would result in better decision-making).
This is also a problem with physical voting: people who show up
at the booths are in many ways different from people who don't
show up, and so the votes are always, to some [unknown] degree,
non-representative.
Interestingly enough, this problem with representation can be
alleviated with electronic votes.
I would expect that, with a set of several opinion polls
conducted both electronically and physically, one could train
a neural network to quite accurately predict the opinions of
people who would show up at the physical polls from the opinions
of people responding to the electronic questionnaire.
Of course, the mixing function for the votes will be different
from arithmetical average, but it the point is, it will work.
This can be taken further.
Similar statistical methods can easily predict the opinions of
people who would _not_ show up at the polls as well, and so
they can represent a much more accurate indicators of the
actual public opinion on a given subject - and with a lot lower
cost, as the price of the software would be offset by not having
most people show up at the polls.
One could also predict what kind of people would show at the polls,
and who wouldn't.
A real indicator of whether a certain decision would serve the
interests of the public, would be the opinion of the public
about the issue _after_ the decision has been taken and brought
some results. This would require some clairvoyance on the part
of the public, though. Currently, people hope that arithmetical
averaging of votes before the decision is the best possible way
to predict their opinion of its results. This expectation seems
ungrounded and most likely untrue. A learned statistical
function may be able to predict future opinions of the general
population from relatively small sample polls much better than
global pre-decision averaging, and thus better represent actual
interests of the public.
The question is, is the society really interested in finding
better ways to realize people's interests, or it is just
perpetuating existing decision-making power structures?
Maybe, somebody could set up such a service, work on the prediction
functions, and then the results would speak for themselves?
This polling service may be combined with some idea futures functions
as well as reputation brokering and collaborative filtering.
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Alexander Chislenko <http://www.lucifer.com/~sasha/home.html>
Extropy Online <http://www.extropy.org/eo/index.htm>
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