[comp.ai.neural-nets] Why "neural nets" is a bad name

wcalvin@well.UUCP (William Calvin) (10/23/87)

     I admit that "nerve nets" and the variant "neural networks" are catchy
titles; we neurobiologists have used the terms quite a lot, though mostly
informally as in the annual meeting called the "Western Nerve Net".  Each real
neural network tends to become its own subject name, as in "stomatogastric"
and "retina", with papers on properties that transcend particular anatomies
incorporated into sessions called "theoretical neurobiology" or some such (I'm
on the editorial board of the JOURNAL OF THEORETICAL NEUROBIOLOGY, often
concerned with networks).
     A quarter-century ago was the era of the Perceptron, the first of the
network learning models.  Various people were simulating network properties
using neuron-like "cells" and known anatomy; when I was a physics undergrad in
1959, I did an honors thesis on simulating the mammalian retina (using anatomy
based only on light-microscopy, using physiology of neurons borrowed from cat
spinal motorneurons, using sensory principles borrowed from horseshoe crab! A
far cry from the CRAY-1 simulations these days using modern retinal
neurobiology).  And if you think that your simulations run slow:  I did
overnight runs on an IBM 650, which had to fetch each instruction from a
rotating drum because it lacked core memory.
     Now this was also the era when journalists called any digital computer a
"brain" -- and I've pointed out that calling any pseudo-neural network a
"neural network" is just as flaky as that 60s journalistic hype.  Now brain
researchers were not seriously inconvenienced by the journalistic hype -- but
I think that blurring the lines is a bad idea now.  Why?
     Real neural networks will soon be a small part of a burgeoning field
which will have real applications, even consumer products.  To identify those
with real brain research may seem innocuous to you now because of the frequent
overlap at present between pseudo-neural networks and simulations of real
neural circuitry.  But these distributed networks of pseudo-neurons are going
to quickly develop a life of their own with an even more tenuous connection to
neuroscience.  They need their own name, because borrowing is getting a bad
name.  Let me briefly digress.
     We are already seeing a lot of hype based on a truly nonexistent
connection to real neuroscience, such as those idiot "Half Brain or Whole
Brain" ads in the Wall Street Journal and New York Times, where "John-David,
Ph.D." describes himself as one of the "world's most recognized 
neuroscientists" recently "recognized as a Fellow by the International
Institute of Neuroscience" (Nope, I've never heard of it either, and I was
a founding member of the Society for Neuroscience back in 1970).  See James
Gorman's treatment in DISCOVER 11/87 p38.  Is this just feel-good floatation-
tank pseudo-psychology dressed up to look like hard science, another scheme to
part half-brained fools from their money?
     Scientists are going to start to get touchy about consumer products
borrowing an inferred plug from real science, just as the FDA has gotten
touchy about white coats in Carter's Little Liver Pills advertisements
attempting to convey medical approval.  And you can bet that, if pseudo-neural
nets become as successful as I think they will, some advertising genius will
try to pass off a nonfunctional product as a neural network "resonating with
your brain", try to get some of that aura of real science and technology to
rub off on the sham.  Do you really want your field trapped in the middle of
an FDA/FTC battle with the sham exploiters because it initiated the borrowing? 
Borrowing a name for a technology from a basic science is not traditional:
civil engineers do not call themselves "physicists".
     We neurobiologists are always having to distinguish the theoretical
possibilities, such as retrograde transport setting synaptic strengths, from
reality.  Those theoretical possibilities may, of course, be excellent
shortcuts that Darwinian evolution never discovered.  And so we'll see
distinctions having to be drawn:  "backpropagation works in pseudo-neural
nets, but hasn't been seen so far in real neural nets."  If you call the
technology by the same name as the basic science, you start confusing
students, journalists, and even experienced scientists trying to break into
the field -- just try reading that last quote with "pseudo" and "real" left
out.
 
                                   William H. Calvin
                                   University of Washington NJ-15
                                   Seattle WA 98195
                                    wcalvin@well.uucp  wcalvin@uwalocke.bitnet
                                    206/328-1192       206/543mulrem