DM: Data Mining's (Machine) Psychological Problem

I thank all those who contributed the "mountain of data" on the =
definition of data mining. The first thing I did in mining the data was =
to write out notes (five pages) on what I thought were the most =
important points made in all of the postings. Then I studied those notes =
several times as I attempted to write out a useful summary of "the =
essence of data mining". That is WHAT I did. HOW did I do it? Honestly I =
don't know much about the 'how' of it. The late BF Skinner said, "If it =
can be verbalized it can be programmed" and that dictum is at least =
mostly true. Given that dictum, if I could verbalize the step-by-step =
way in which I did this data mining I could pass it on to the computer =
code writers who could then turn it into a useful piece of software. =

Exercises with definitions are important. Every statute here begins with =
a set of definitions. Recently a man in Ontario won a court case by =
saying that according to standard law dictionary definitions he was a =
"natural person" and not a "legal person" and therefore the court had no =
jurisdiction. Perhaps the judge was amused...and ruled in his favour. Of =
course my effort at "natural data mining" may be more amusing than =
useful. And you are the judges.

    I can verbalize some of this process without much effort at =
"introspection". For example, if I found some words like "The definition =
of data mining is...." I would make a note. Similar efforts to get right =
to the essence of data mining were also noted. With a little more =
introspection I could probably come up with a list of key words I used. =
But I also made notes of particular or specific points about data mining =
techniques which I thought might shed some light on the essential =
features. I don't know what criteria I used to select those units. I =
also don't know if I could discover it even with a lot of introspection.

    "Homo sapiens" indeed. "Robo sapiens" (couldn't resist that one) is =
much more cognizant of its (artificial) intelligence in that a robot =
could be programmed to spell out in fine detail every machine step as it =
processes data. Right down to the movement of electrons. We humans =
really aren't very self-aware. Some of us, however, are more self-aware =
than others and the self-awareness may be general or specific.

    There are some very interesting "big problems" in robotics and AI and =
Skinner's dictum applies to them. Two other big problems have to do with =
developing a general learning program (glp) and a conversational program =
(cp) which would meet the criterion of human equivalency. In both cases =
I would say that it is reasonable to ask the experts to come up with the =
necessary verbalizations to prepare the way for code writing. Not an =
easy task, but "doable". In the case of a glp I would ask psychologists =
and educators as well as machine learning experts. In the case of a cp I =
would ask linguists, translators and clinicians who teach patients how =
to converse and interact socially.

    A general data mining program (gdmp) would have enormous value. Isn't =
that what all of this work ultimately is expected to achieve? But who =
could verbalize how we discover that which is important in the =
"mountains of data" on our computer screens? Again we ask, "Who are the =
experts?" In the case of data mining it sounds to me like the experts =
are "good students" in a huge variety of fields. Not necessarily good =
teachers or people good at setting up data files and displays. But we do =
know there are people who can speed through mountains of data in =
commerce with understanding, or mountains of data in medicine, or =
computing science, etc. Beyond that we know that among those "good =
students" some will be more cognizant of HOW they do WHAT they do than =
others. When this kind of good student studies all those statistics and =
graphs and verbal reports in commerce, he or she quickly arrives at a =
useful and understandable rendition for what is initially confusion. If =
we can then find the good students who also have unusually high =
INTROSPECTIVE ABILITY and enlist their co-operation as they do "natural =
data mining" with a variety of subjects we may be able to arrive at a =
gdmp in a verbal form first and then convert it to a computer program.

    Well, that's about the best I can do to this point. Of course the =
gdmp would be expected to evolve, step-by-step as all these programs are =
written, as is happening now. Any guestimates as to how long it would =
take to arrive at a gdmp in that manner? Any other suggestions as to how =
one could go about it with a single mega-project? Any fallacies in the =
reasoning above re finding these "good students with high introspective =
ability who are willing and able to report verbally on their =
introspections?"
FWP

http://users.uniserve.com/~culturex/Machine-Psychology.htm

PS-As an aside, any comments on Neugents software with its ubiquitous tv =
ads? See http://www.cai.com/neugents

The tv ads tell us "this is the first software that can think" and the =
web site says "This on-going self-learning process...can acquire far =
more knowledge than any expert in any field". These are astonishing =
claims. If taken literally, Neugents is already a gdmp which can acquire =
the knowledge we seek even better than human experts in any field. We =
are told it "...has the capacity to learn, accumulate knowledge and =
apply this knowledge to new situations". That being so, it is more than =
a gdmp. It can learn more broadly and apply this knowledge to new =
situations. Since "Neugents learn by observation"
why could they not be used as the software for a robot cognitive =
sub-system in conjunction with a recognition sub-system, ie "machine =
vision/machine perception"

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