From: Emlyn O'regan (oregan.emlyn@healthsolve.com.au)
Date: Mon Mar 18 2002 - 15:51:18 MST
Have you ever noticed how some kids can kick any adult's backside at many
computer games, including complex sims like the Sim City family, where they
can't even be expected to understand a lot of the concepts (eg: marketing,
demographics).
Discounting the possibility that kids have more time to practise (which is a
reasonable assumption, but hey), I wonder whether kids are good at some of
these games precisely because they don't understand what is being modelled?
While an adult who understands economics might approach a sim as though it
behaves like the real world, a kid would have to discover the behaviour of
the sim, completely divorced from its status as a model.
Similarly with the story below, are those who are naive about the stock
market better able to take on board observed patterns, and less weighed down
by expectation about how the market *should* behave?
I wonder if, with all the simulation computer games out there now, and
massively multiplayer games, we are training our kids to understand complex
systems in a deeper, though more intuitive way, than their elders do?
Emlyn
> -----Original Message-----
> From: steve [mailto:steve365@btinternet.com]
> Sent: Tuesday, 19 March 2002 12:33 AM
> To: extropians@extropy.org
> Subject: Random choice versus computer models.
>
>
> http://www.guardian.co.uk/Archive/Article/0,4273,4373847,00.html
>
> A story that's both amusing and interesting. It involves an
> experiment in
> which a professional investment analyst, an astrologer and a
> five year old
> girl were each given a notional sum to invest in the
> stockmarket. After a
> year the five year old had a score of plus 5.8%, the
> astrologer had minus
> 6.2% and the analyst minus 46.2 (the stock market as a whole
> had minus 16%.
>
> Quite apart from giving us the opportunity to laugh at the
> discomfiture of
> the the analyst - schadenfreude is wonderful - this does
> raise yet again the
> interesting question of prdicting the outcome of complex
> systems. Steve
> Davies.
>
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