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AIList Digest Volume 5 Issue 087
AIList Digest Wednesday, 25 Mar 1987 Volume 5 : Issue 87
Today's Topics:
Policy - American Militarism,
Comments - Limitations of AI/Expert Systems & Explanation Capability,
Application - Analysis of Unknown Data
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Date: Fri, 20 Mar 87 14:28:46 +0100
From: mcvax!cwi.nl!tomi@seismo.CSS.GOV (Tetsuo Tomiyama)
Subject: Policy - American Militarism
In Article 1432 of mod.ai, Chris Elsaesser (elsaesser%mwcamis@MITRE.ARPA)
submits a Call for Papers
> Issues Concerning AI Applications To Battle Management
>
> University of Washington
> Thursday, July 16, 1987
>
> Sponsored by AAAI
>
> Success in applying AI technologies to battle management (e.g., production
> and blackboard systems for sensor fusion, constraint propagation for
> non-temporal planning tasks) has generated growing interest in the defense
> community in developing intelligent battle management aids, workstations,
> and systems. Along with this growing interest, there has been an order of
> magnitude increase in funding for battle management AI projects (e.g.,
> Army-DARPA's Air-Land Battle Management, SAC-JSTPS-RADC-DARPA's
> .......
First of all, I really feel doubts about the policy of AAAI to sponsor
such a BLOODY nonsense, but since this is not the right place to
criticize AAAI, I don't write about it. (Since I am a member of AAAI,
I reserve my right to do so, though.)
Now, I am strongly against such a posting circulated ALL AROUND THE
WORLD through the net. Of course, I personally do hate such BLOODY
research and at least I won't do such things. But, this is absolutely
my personal opinion and I know that anyway I don't have power big
enough to stop it. So, as far as it remains an AMERICAN MATTER, I
don't bother guys over there.
However, mod.ai is broadcasted to all over the world and I really do
not want to see OUR computer networks are used to promote such BLOODY
NONSENSE which may contribute only to destroying everything. I think
this kind of postings should be even prohibited from the world wide
net distribution. You (in plural) should be aware that there are lots
of people who work hard for peace and many scientists and engineers are
against the use of modern technology for military purposes even in the
American AI community.
--Tetsuo Tomiyama (UUCP: tomi@cwi.nl)
[I don't believe that this message is offensive to the general AI
community. I regret that it offends you, but can't censor all
such material to suit your preferences. I can only offer you the
same channel for stating your own position.
AIList is a global channel. It could be limited to just the Arpanet,
as it once was, but that would not be in the best interest of all
involved. -- KIL]
------------------------------
Date: Mon, 23 Mar 87 18:04:56 +0100
From: mcvax!cwi.nl!tomi@seismo.CSS.GOV (Tetsuo Tomiyama)
Subject: Re: Re: Submission to mod.ai
[...]
I am not saying that you are prohibited from military research. I am
saying that it is all up to you whether you take part in military
research or not. However, since there are people who do not like
military research, just like there are people who do not want to see
pornography in public or who do not want to get somebody else's smokes
in a public space, you should not at least promote military research in
public.
I propose, therefore, to submit postings relevant to militarism should
NOT be PROHIBITED but at least requested to be MARKED as military
related article at the responsibility of original authors (rather than
by the moderator), just like advertisements from tobacco companies, so
that if I don't want to read it I can skip it.
[...]
... so please give us a method to recognize military related
articles as soon as possible.
--Tetsuo Tomiyama (UUCP: tomi@cwi.nl)
[This is the first time this matter has come up in four years
of AIList. It does not seem to be a problem for the vast majority
of readers, but you are welcome to try convincing submitters
of defense-related messages to add a keyword to their headers.
AIList is primarily an Arpanet discussion list. The Arpanet
was developed by the military, is supported by the military,
and is intended for defense-related communication among
military contractors. One could assume that all Arpanet
messages are military in nature, although that heuristic
does not seem very useful in the case of AIList. What is
really needed here is an intelligent mail reader that screens
your messages and adds the appropriate keywords. -- KIL]
------------------------------
Date: Mon, 23 Mar 87 13:35:16 cst
From: lugowski%resbld%ti-csl.csnet@RELAY.CS.NET
Subject: Oxymoron: Real-time Knowledge-Based Nurse/Nuclear Plant
Operator
Regarding the following...
Date: 22 Mar 1987 18:21-EST
From: cross@afit-ab.arpa
Subject: Conference - AAAI-87 Workshop on Real-Time Processing
Workshop on Real-Time Processing in Knowledge-Based Systems
AI techniques are maturing to the point where application
in knowledge intensive, but time constrained situations is
desired. Examples include monitoring large dynamic systems
such as nuclear power plants... sensor interpretation and
management in hospital intensive care units...
Desired by whom? I wouldn't trust AI techniques with monitoring large dynamic
systems of the class of a medium-sized municipal toilet. I would certainly
want out of any ICU where my fragile well-being did not depend on an ICU
nurse, overworked as though he or she may be. The AI community has had up
to now the good sense of relegating its really questionable achievements to
the battlefield, where they are fondly appreciated. Let's not get too greedy
by introducing the battlefield to our rather safe nuclear plants and ICUs.
-- Marek Lugowski
Texas Instruments
lugowski%crl1@ti-csl.csnet
------------------------------
Date: 22 Mar 87 21:14:25 GMT
From: tektronix!tekcrl!vice!tekfdi!videovax!dmc@ucbvax.Berkeley.EDU
(Donald M. Craig)
Subject: Re: AI Project Information Request
Well, I'm probably over reacting to what will end up being
nothing more than a spelling checker, but I find the thought
of having creative writing graded by a computer program appalling.
It's particularly pernicious in the public school system,
where penalties for failure to conform to some computer
program's judgement of style and content are brought to bear.
The best and most universal writing is about the human condition.
What does a computer program (or indeed its artificially
intelligent author) know about that? What would it do with...
James Joyce? William S. Burroughs? Anthony Burgess? Ogden Nash?
What would happen to literary experiment?
Would there be an image processing version that graded Picasso?
It's bad enough that some smartass robot comes up to me at
trade shows pedalling product, or some auto-dialer phones
me while I'm in the shower to sell carpet cleaner, but
these uppity machines I can be rude to and ignore. The one
that's marking my school essays I cannot.
In law I have the right to be judged by a jury of my peers.
In school I demand that same right. I will NOT be judged by
a machine.
Yours for a better tomorrow,
Don Craig
Whose opinions are his own.
--
Don Craig dmc@videovax.Tek.COM
Tektronix Television Systems ... tektronix!videovax!dmc
------------------------------
Date: 23 Mar 87 15:22:32 GMT
From: mcvax!ukc!warwick!gordon@seismo.css.gov (Gordon Joly)
Subject: Explanation and Justification.
In answer to the question "does an expert system need to
be able to explain itself to be useful", consider teaching.
Anyone who has taught knows, to teach something (ie to explain
it to a class), you really need to understand the issues,
before you can begin to get them across. Also, in the process
of teaching itself, ones own understanding is often deepened.
Gordon Joly -- {seismo,ucbvax,decvax}!mcvax!ukc!warwick!gordon
------------------------------
Date: 18 Mar 87 20:48:17 GMT
From: hpcea!hpfcdc!hpldola!hpldolm!ben@hplabs.hp.com (Benjamin
Ellsworth)
Subject: Re: analysis of unknown data
I have two comments on this discussion; the first is general the second
is specific.
My first comment on this whole discussion, as I understand it, is that
it is silly. We are being asked to find "the" meaning of some large
file without any context for the file. Is it text? Is it integer
data? Is it floating point data? Is it encrypted in any way? The
search for meaning in the absence of context is a waste of time.
(In essence, I agree with M. B. Brilliant as follows.)
What is meaningful in one context is often not meaningful in another.
However, sometimes, it is. A file full of integer measurement data will
usually be indistinguishable from a file of a bit-mapped color image.
A bunch of integers is a bunch of integers (unless some *recognizable*
context information is included). If you take a group of integers and
make a pretty picture with them, what will you do when I tell you that
they were process measurements from a ball-bearing factory? What will
you do when you interpret a Mandelbrot image as a bad lot of wafers
in an otherwise well controlled fab?
I'm sure that you would like to say that you can't make a pretty
picture with ball bearing data. Perhaps not in every case, but I know
of a gentleman who *sells* "art" generated from HP stock performance
data. He has given some stock data meaning in a new context.
The best response to this question was the one from Mr. Adrian
who suggested that you look for the context(s) that the file
was used in. If you can't find the correct context, you cannot
ascertain the correct meaning. If the data exists in a vacuum, you can
choose whatever context that you wish and with enough massaging you
can make the data meaningful.
Second comment:
> Testing for randomness might be the first test; sure would save
Random is too loose of a term. Are they "random" samples from a
uniform distribution, or "random" samples from a Gaussian distribution?
In either case is the distribution a real population, or a mathematical
model of a distribution function?
I don't want to sound like a flame, but testing for randomness is
ridiculous! You *cannot* prove a set of data to be "random." In fact
the key to some encryption schemes is to make a dataset appear "random"
to most simple minded tests. This does not mean that there is no
information in the data. It just means that the context of the
information is well hidden from such simple minded filters.
What you are saying when you say that you will test for randomness is
that you will test to see if the data is meaningful in any known
context. Do you know all possible contexts? Will you live long enough
to test for all of them? What happens when the data is meaningful in
more than one context?
---------
Benjamin Ellsworth
hplabs!hpldola!ben
(303) 590-5849
P.O. Box 617
Colorado Springs, CO 80901
2+2=4 (void where prohibited, regulated, or otherwise restricted by law)
------------------------------
Date: 23 Mar 87 19:01:10 GMT
From: dave@mimsy.umd.edu (Dave Stoffel)
Subject: Re: analysis of unknown data
In article <11160001@hpldolm.HP.COM>, ben@hpldolm.HP.COM (Benjamin
Ellsworth) writes:
> My first comment on this whole discussion, as I understand it, is that
> it is silly. We are being asked to find "the" meaning of some large
> file without any context for the file. Is it text? Is it integer
> data? Is it floating point data? Is it encrypted in any way? The
> search for meaning in the absence of context is a waste of time.
Maybe I am at fault for inadequately describing the problem,
but it is neither silly nor a waste of time. Apart from these
two comments and the later one about test for randomness being
ridiculous, Ben's comments are helpful in further detailing the
possibilities.
> What is meaningful in one context is often not meaningful in another.
> However, sometimes, it is. A file full of integer measurement data will
> usually be indistinguishable from a file of a bit-mapped color image.
> A bunch of integers is a bunch of integers (unless some *recognizable*
> context information is included). If you take a group of integers and
> make a pretty picture with them, what will you do when I tell you that
> they were process measurements from a ball-bearing factory? What will
> you do when you interpret a Mandelbrot image as a bad lot of wafers
> in an otherwise well controlled fab?
> I'm sure that you would like to say that you can't make a pretty
> picture with ball bearing data. Perhaps not in every case, but I know
> of a gentleman who *sells* "art" generated from HP stock performance
> data. He has given some stock data meaning in a new context.
I wouldn't like to say you can't have multiple representations of
a set of data poin
However, one man's "art" is simply another man's pictoral or
imagic presentation of stock data. (Particularly if the raw
stock data was not convaluted by the artist). In fact, it might
be a useful presentation for certain kinds of trend analysis.
> The best response to this question was the one from Mr. Adrian
> who suggested that you look for the context(s) that the file
> was used in. If you can't find the correct context, you cannot
> ascertain the correct meaning. If the data exists in a vacuum, you can
> choose whatever context that you wish and with enough massaging you
> can make the data meaningful.
Certainly there is a pitfall in the analytic process; one may
"discover" meaning that was not the intent of the creator of
the data. So it goes, sometimes.
"finding the correct context" and "finding the meaning" are the
same thing!
> Random is too loose of a term. Are they "random" samples from a
> uniform distribution, or "random" samples from a Gaussian distribution?
> In either case is the distribution a real population, or a mathematical
> model of a distribution function?
> I don't want to sound like a flame, but testing for randomness is
> ridiculous! You *cannot* prove a set of data to be "random." In fact
> the key to some encryption schemes is to make a dataset appear "random"
> to most simple minded tests. This does not mean that there is no
> information in the data. It just means that the context of the
> information is well hidden from such simple minded filters.
Hmm. I think what I mean is that if the data set appears to be a Gaussian
distribution, then I'm not going to apply any other tests.
> What you are saying when you say that you will test for randomness is
> that you will test to see if the data is meaningful in any known
> context. Do you know all possible contexts? Will you live long enough
> to test for all of them? What happens when the data is meaningful in
> more than one context?
I can't possibly imagine all conceivable or theoretic contexts. I
can imagine too many to try. I am looking for an analytic process
that is more efficient than enumerating all the context tests I can
imagine. If multiple context tests yield "reasonable"
representations, I might just have to flip a coin or allow for all
interpretations.
I never said that the data has no context! I simply said that I
don't know a-priori what its context is. It *is* the case that data
points can be analysed in the absence of knowledge of the structure of
the function which produced them. The object is to detect patterns,
if possible, and search for "meaningful" interpretations.
Some of the discussion of this subject sounds like the participants
are frustrated by these two facts:
1. I *won't* live long enough to apply every possible context
test. (Discovery by enumeration).
and
2. they don't know of any more efficient methodology than discovery
by enumeration, ergo the problem is silly or a waste of time.
--
Dave Stoffel (703) 790-5357
seismo!mimsy!dave
dave@Mimsy.umd.edu
Amber Research Group, Inc.
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End of AIList Digest
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