 Millions
of years ago, out of a primordial sludge consisting of water,
saline, and amino acids, arose life forms. Through the course
of evolution and natural selection, some of these life forms
evolved into rational, thinking beings (others, of course,
became nearly-elected leaders).
Today,
a similar process is taking place right here on the Web. Out
of a primordial sludge consisting of chat rooms, tiny wireless
cameras, and Spice Girls fan pages, a new life form is being
born which may well evolve into a new kind of rational, thinking
consciousness. Either that or we've got a new presidential
candidate for 2004.
Making
the Implicit, Explicit
The
force behind this new brain is the Mindpixel Corpus. With
their vaguely perplexing motto, "Making the implicit,
explicit," Mindpixel's aim is to gather millions and
millions of simple human observations which are true regardless
of race, gender, or individual differences, and compile them
into a working model of the human mind.
Here's
how it works.
Visitors
are encouraged to submit what the Mindpixel people call "a
binary statement of consensus fact such as 'Water is wet'
or 'It is difficult to swim with ski pants on'." These
statements are called "mindpixels."
Upon submitting
your entry, ten previously submitted mindpixels appear which
you are asked to rate according to their truth and value.
The truth rating of the statement is a simple "True"
or "False," the value rating is a five-unit scale
from "Poor" to "Excellent."
The plan
is to gradually create a "brain" comprised of individual
units of human experience, graded according to consensus and
reliability.
You
Don't Know GAC!
 The
brain being created in this grand experiment is called "Generic
Artificial Consciousness," or GAC (pronounced "Jack").
The project
head is Dr. Robert Epstein, which the Mindpixel site calls
"one of the world's leading experts on human and machine
behavior." Dr. Epstein has a psychology doctorate from
Harvard (1981), is the founder and Director Emeritus of the
Cambridge Center for Behavioral Studies in Massachusetts,
and is Adjunct Professor of Psychology at San Diego State
University.
In its
first year on-line, the Mindpixel Corpus has received nearly
8 million individual measurements of more than 355,000 individual
items of "human consensus experience" from contributors.
Upon the completion of its collection phase in 2010, work
will begin to create a statistical model of an average human
mind with the aim of using it as a foundation for true artificial
consciousness.
And the
whole thing is possible only because of the Web. Without the
aid of the Internet, the data entry alone would have cost
$250 million.
This
Translator Definitely Needs A Union
Will it
be successful? To his credit, Dr. Epstein isn't sure. "We
don't know if it is possible to build a normal personality
out of millions of little pieces. This experiment will tell
us how reasonable the idea is."
Of course,
whether or not it succeeds depends largely upon how we define
"success." If by "success" we mean the
creation of a truly artificial consciousness, many experts
believed it is probably doomed to failure. They claim that
electronically storing millions of simple statements about
experience, and processing them according to an established
set of rules is no more likely to produce consciousness than
doing the same thing with statements written on pieces of
paper.
One long-standing
argument against the belief that consciousness is inherently
a rule-defined processes is John Searle's "Chinese Room
Argument."
In this
thought-experiment, a man is locked into a room with nothing
more than a book of complex rules. Through a slot in the door
come slips of paper upon which are written Chinese words.
The man compares these symbols with his rule book, writes
down the result (which is an English translation), and shoves
it back through the slot.
The point
Searle is making is that nowhere in this entire system is
there any actual understanding of Chinese. In other words,
mental states, such as the understanding of language, cannot
be created by a system of input and output rules, even
when a human consciousness is involved as part of the system.
(See sidebar).
If, on
the other hand, we consider "success" to mean the
creation of a system which will emulate and mirror the human
consciousness in ways that can improve our understanding,
then there is every reason for hope. Mechanical models (be
they levers and cranks or electrons and silicone) have a long
history of providing invaluable insights into the way minds
work.
Survey
Says ...
If nothing
else, GAC could completely revamp the way we conduct polls
and surveys. No need for dozens of employees to phone thousands
of average citizens to discover which product name they like
better — soon we can just ask GAC.
Of course,
we'd have to know exactly what GAC's "demographic"
is. In other words, we'd have to find out just what kind of
"person" is residing in GAC's virtual mind.
 Fortunately,
even as I write these words, GAC is undergoing a months-long
psychological test. In fact, GAC will be the first machine-based
artificial personality to be tested by the MMPI (Minnesota
Multiphasic Personality Inventory), which is the same test
used in both corporate hiring practices, and criminal court
proceedings.
It will
be interesting to see whether GAC turns out to be an ideal
CEO, or found "not guilty by reasons of insanity."
Reprinted
from Circa2000, May 16, 2001.
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John
Searle's Chinese Room Argument
Against
"strong AI," Searle (1980a) asks you to imagine
yourself a monolingual English speaker "locked in a room,
and given a large batch of Chinese writing" plus "a
second batch of Chinese script" and "a set of rules"
in English "for correlating the second batch with the
first batch."
The rules
"correlate one set of formal symbols with another set
of formal symbols"; "formal" (or "syntactic")
meaning you "can identify the symbols entirely by their
shapes." A third batch of Chinese symbols and more instructions
in English enable you "to correlate elements of this
third batch with elements of the first two batches" and
instruct you, thereby, "to give back certain sorts of
Chinese symbols with certain sorts of shapes in response."
Those
giving you the symbols "call the first batch 'a script'
[a data structure with natural language processing applications],
"they call the second batch 'a story', and they call
the third batch 'questions'; the symbols you give back "they
call . . . 'answers to the questions'"; "the set
of rules in English . . . they call 'the program'": you
yourself know none of this. Nevertheless, you "get so
good at following the instructions" that "from the
point of view of someone outside the room" your responses
are "absolutely indistinguishable from those of Chinese
speakers." Just by looking at your answers, nobody can
tell you "don't speak a word of Chinese."
Producing
answers "by manipulating uninterpreted formal symbols,"
it seems "[a]s far as the Chinese is concerned,"
you "simply behave like a computer"; specifically,
like a computer running Schank and Abelson's (1977) "Script
Applier Mechanism" story understanding program (SAM),
which Searle's takes for his example.
But in
imagining himself to be the person in the room, Searle thinks
it's "quite obvious . . . I do not understand a word
of the Chinese stories. I have inputs and outputs that are
indistinguishable from those of the native Chinese speaker,
and I can have any formal program you like, but I still understand
nothing." "For the same reasons," Searle concludes,
"Schank's computer understands nothing of any stories"
since "the computer has nothing more than I have in the
case where I understand nothing" (1980a, p. 418). Furthermore,
since in the thought experiment "nothing . . . depends
on the details of Schank's programs," the same "would
apply to any [computer] simulation" of any "human
mental phenomenon" (1980a, p. 417); that's all it would
be, simulation.
Contrary
to "strong AI", then, no matter how intelligent-seeming
a computer behaves and no matter what programming makes it
behave that way, since the symbols it processes are meaningless
(lack semantics) to it, it's not really intelligent. It's
not actually thinking. Its internal states and processes,
being purely syntactic, lack semantics (meaning); so, it doesn't
really have intentional (i.e., meaningful) mental states.
For more,
click
here.
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Rebutting
the Chinese Room Argument
Naturally,
those who believe in "Strong AI" (meaning artificial
intelligence that actually has consciousness rather than merely
mimicking it) have developed many counter arguments to Searle's
Chinese Room. Although differing in approach, the basic strategy
underlying these arguments is essentially the same and can
best be described as "throwing sand in the opponent's
eyes."
For an
example, read Larry Steven Hauser''s dissertation against
Searle here.
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