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                  The Next Wave of MT Publicity

                          By Alex Gross

             (Originally published in the ATA Chronicle,
                            July, 1994)


     The year is 1986, and I am sitting on my floor with my
hacker genius friend, whom I'll call Mike.  We are discussing the
imminent wave of Artificial Intelligence programs which will soon
take over the world and make us both vastly rich.  In this
venture I will provide the practical knowledge, Mike the
programming skills.  I am eager to put together a medical
application, and Mike has some ideas of his own.  We both believe
there is no limit to the power of AI to harness ideas, learning,
knowledge.  Mike idly picks up a Roget's Thesaurus lying on my
floor and leafs through it.

     "You see how easy it is, Alex" he tells me, "All we need is
the French equivalent of this book, I link them together with a
program, and bingo: perfect Machine Translation!"  I am hesitant
and attempt to express my doubts.  I try to tell Mike that it
isn't that simple, but he will have none of it.  He is supremely
sure that language is a pushover, what programmers call a
"trivial task."

     Mike never built his MT system, even though he did go on to
write an award-winning AI application that came closer than any
to passing the Turing Test (more about that test later).  So
there is no doubt about his programming skills, nor those of many
other programmers.  What remains in doubt is the capacity of
these highly specialized technicians to assess the deepest
problems connected with MT, AI, and NLP (Natural Language
Processing) applications in general.

     Publicity about MT has come in waves.  The first wave was
launched by Turing, Weaver, Shannon, and other computer pioneers.
A later wave emanated from IBM around the time of the 1964
World's Fair.  The most recent wave started in the mid-Eighties
and has culminated in the various micro and mainframe systems now
familiar to  us.  Each wave has publicized much the same
arguments:

     1.  MT will be faster than human translators.
     2.  MT will be more accurate than human translators.
     3.  MT will be cheaper than HT (though more
          recently this claim has been slurred over).
     4.  MT will break the language barrier and open the
          way to true and lasting human understanding (this
          point has also been deemphasised of late, though
          early enthusiasts greatly stressed it).


     Soon the next wave of MT publicity will burst upon us, and
the publicity mills are already gearing up. (1)  In a year or two we
will be reading about the incredible breakthroughs achieved by
the "CYC" project, a unique Natural Language Processing
experiment using massive parallel processing to build the
supposed eight to ten million links embedded in human language.
CYC supposedly comprises an "EnCYClopedia" of what we have all
learned about the world around us.  Once again all the familiar
arguments about MT are likely to resurface.  Even though CYC is
not an MT system in itself, any success it enjoys will certainly
reach out to embrace MT and other branches of AI.

     There can be no doubt that the CYC project is an important
one worthy of attention by all translators.  For this reason--and
also because its home base is Austin, Texas--I have asked Peter
Krawutschke to determine if it will be possible for a group of
computer-oriented ATA members to look in on CYC while we are in
Austin this October.  Perhaps it could also become possible for
representatives of CYC to take part in our conference program.

     The arguments for and against MT seem to come and go in an
almost cyclical fashion, and some translators have come to view
this subject with apprehension.  But we need to pay attention to
what is happening in MT and AI in general.  Two unassailable
arguments in its favor remain: 1) no one opposes MT where it
really works, and 2) MT works quite well for those tasks where it
is suitable.  The main questions concern which tasks these may
be, whether their number may grow, and how translators will come
to be integrated into the overall continuum of MT, Computer
Assisted Translation, and traditional techniques.

     But as my friend Mike's attitude towards language shows,
there are still some larger concerns about MT, which have dogged
its development from its very beginnings and remain very much
with us.  Underlying the basic assumptions of MT are much the
same notions often vocalized as "Why don't you just type it out
in Spanish?" or "Just look at it and say it in English."  What MT
shares with such solecisms is the notion that the differences
between two languages can easily be predicted and routinized.
Noam Chomsky's concepts of "deep structure" or "universal
grammar" reflect the same fallacies, in this case beefed up with
many layers of academic terminology.  Basic to all these
approaches is the half-truth that language is inherently
reasonable, which must be balanced against the other half-truth,
that it is not reasonable at all.  It is altogether possible--as
I have argued elsewhere (2)--that on an evolutionary plane language
may be at least partially an outgrowth of the spray marks used by
animals to claim territory, attract mates, or repel rivals.

     Similarities between MT and other coequal branches of AI--
"voice-writing," text retrieval, robotics, Machine Vision--also
cannot be overstressed: all have fallen behind schedule for
closely related reasons.  Voice-writing--which was originally
supposed to catch every nuance of speech automatically--has now
settled for asking the speaker to confirm or correct it following
every word or phrase.  Text retrieval has still not fully
recovered from the ambitious claims made surrounding its birth.
One thing the computer does best is to match up strings of text,
though this was never strictly speaking "AI."  But anything less
than a perfect match requires what is called a "fuzzy search,"
which in turn often produces vast quantities of "quasi-results"
requiring highly qualified humans to determine their relevance.
This means we are still a long way from truly reliable research
based on a given text base.  This is because searching according
to "key-words" is only as accurate as the key-words which have
been entered.  In other words, a search through a legal data base
under the heading "Teenage Abortion" will not find:

     JUDGE:  Did you have the baby?
     REPLY:  No, I decided not to.

     Robotics, envisioned as supplying us all with unlimited
household servants, did not even succeed completely in taking
over the factory floor--rather, the factory floor had to be
redesigned from scratch to allow robots to work.  And one still
hears the story of the two Japanese welding robots who during a
lull have been known to start welding each other.  Even Isaac
Asimov, the father of Robotics, expressed his disappointment that
these machines were not robots as he envisioned them.  And as for
Machine Vision, how many people are ready to have a computer make
the next left turn for them, much less drive them off into the
sunset?

     Like Asimov, even AI's primary advocate, Marvin Minsky, has
taken to writing science fiction to promote his ideas, which
begin to sound indeed more and more like SF and less like viable
proposals.  And even Minsky is now hedging on the future of MT,
as this account of instant Japanese-English interpreting from his
The Turing Option (co-authored with Harry Harrison) illustrates:

     "He touched the phone disconnect button and the voxfax
     machine behind him instantly sprang to life, humming lightly
     as it disgorged the printed record of their phone
     conversation.  His words were in black, while Mura's were in
     red for instant identification.  The translation system had
     been programmed well, and as he glanced through it he saw no
     more than the usual number of errors.....The staff
     translator would later verify the correctness of the
     translation the computer had made." (3)

     Of course this wondrous machine had already made a real-time
onscreen "rough," though some may wonder what "the usual number
of errors" was and how the protagonist recognized them without
himself being an expert translator.  (And if he were, why would
he have needed this device in the first place?)

     Thus, even science fiction has partially given up on old-
fashioned, red-blooded AI.  The whole point of the Turing Test
was to make a computer so lifelike that those communicating with
it via keyboard from another room would actually believe they
were talking to a human.  No machine has yet fully passed this
test, which has since been subjected to many doubts and
objections--even Alan Turing himself never supposed such a ruse
could be maintained for more than a few minutes (4).  And so the
days of the completely human computer may belong to the past
rather than the future, except for those who believe that all
sci-fi alternate futures are equally true.

     No doubt some readers will regard this fairly accurate
description of the state of AI art as a sacrilege, as a certain
religious element has come to creep into some discussions about
the computer.  Those who venture any skepticism at all--critics
like Hubert Dreyfus or John Searle or Joseph Weizenbaum--have
sometimes been dismissed as simple-minded "Luddites," though
recent research has shown that the true Luddites were far from
simpletons (5).  Some of our experts seem so wedded to their vision
of themselves as the shapers of the future that they are unable
to notice any shortcomings in their outlook.

     Engineering has often succeeded by breaking down large
problems into smaller pieces, finding the solution for each one,
and then fitting the pieces back together again.  If this
approach appears to fail, it can only be that the pieces were not
made small enough--or perhaps inadequate funding.  If massive
parallel processing fails to solve the problem, Neural Nets or
Markov Models or DNA-etched microchips or nanotechnological brain
implants are sure to take care of it.  The notion that language
may not be susceptible to these approaches--that its semantic-
contextual patterns may still fall through the holes of their
mapping methods--is a foreign one for many computer scientists.

     As the coming flood of MT, AI, and NLP rhetoric breaks over
our heads once again, it is perhaps important that we all of us
recognize it for what it is: often little more than a form of
advertising.  There are also some grounds for supposing that
translators are not even supposed to hear any of this.  The real
target for all the shouting is probably a combination of MIS
directors (Management Information Services), office managers, and
other executives in large corporations (6).  These highly paid
officers usually know next to nothing about language or
translation and little enough about computers.  What many of
these MT vendors will be selling is not so much "Translating A
Foreign Language" as "The Idea Of Translating A Foreign
Language."


NOTES:

     1 CYC-O, Doug Lenat's Quixotic Quest to Create an Artificial
Intelligence with Common Sense, Interview by Jeffrey Goldsmith,
WIRED, April, 1994, p. 94.

     2 Language and MT: Conflicting Technologies? Scitech
Translation Journal, October 1993.

     3 Minsky, Marvin & Harrison, Harry: The Turing Option,
p. 6, Warner Books, 1993.

     4 Unlike some of his followers, Turing was quite relaxed
about this test and foresaw nothing more startling than that "an
average interrogator will not have more than 70 per cent chance
of making the right identification after five minutes of
questioning."  Elsewhere he waxed whimsical and proposed that the
computer should try to deceive an interrogator by pretending to
be a woman, while a real woman would make the same claims from
another room.  Thus, the so-called Turing Test, intended to
identify "true AI," is not--unlike many testing procedures in the
physical and even biological sciences--constructed in a rigorous
way.  (Andrew Hodges: Alan Turing: the Enigma, pp. 415-17,
Touchstone Books, Simon and Schuster, 1983).

     5 Whole Earth Review: Robert Rossney, The New Old Luddites,
Spring, 1994, pp 2-12; Reid, R.W: Land of Lost Content: the
Luddite Revolt, 1812, Heinemann, 1986.

     6 Perhaps symptomatic of this movement, a magazine called
Multilingual Computing has been in existence for over a year,
though very few copies have reached translators.  Slick and well-
written on its own level, it is evidently directed towards a
corporate audience from a small town in Idaho.  For more
information, contact: Multilingual Computing, 111 Cedar Street,
Suite 5, Sandpoint, Idaho 83864, Tel: [phone], Fax (208)
263-6310.

            Copyright, 1994 and 1995 by Alexander Gross

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