Path: utzoo!utgpu!jarvis.csri.toronto.edu!rutgers!usc!elroy.jpl.nasa.gov!ucla-cs!uci-ics!zardoz!tgate!ka3ovk!drilex!axiom!linus!mbunix!bwk
From: bwk@mbunix.mitre.org (Barry W. Kort)
Newsgroups: comp.ai
Subject: Re: IQ is not static, genetic differences inconsequential.
Summary: Consider the analogy of the Math Coprocessor
Keywords: Learned vs. hardwired.
Message-ID: <62227@linus.UUCP>
Date: 3 Aug 89 10:50:55 GMT
References: <3549@csd4.milw.wisc.edu> <4431@uhccux.uhcc.hawaii.edu> <485@edai.ed.ac.uk> <1785@uceng.UC.EDU>
Sender: news@linus.UUCP
Reply-To: bwk@mbunix (Barry Kort)
Organization: The Ferchacta Corportation, Shipinport, MA
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One way to think about the debate between genetically inherited
ability versus education and training is to consider the
analogy of the math co-processor or floating-point accelerator.

My computer can do floating point math by using software
routines running on its native CPU.  But it can perform
better with floating-point hardware.  

Similarly, a dancer or athlete can execute her routine using
step-by-step conscious instructions.  Or she can compile her
routine into the cerebellum, where it becomes "second nature".

It is clear that the presence of an appropriately engineered
neural network (e.g. cerebellum) or an appropriately designed
processor (e.g. floating point accelerator) confers a
performance advantage.  Those unfortunate enough to have
inherited selective dysfunctions exhibit corresponding
degradations in performance.  In rare cases, education and
training can yield results superior to performance of
unimpaired hard-coded systems.

--Barry Kort