The Literary Engine
In Gulliver’s Travels,
Jonathan Swift made light of devices that create language automatically and
randomly. The engine was meant to parody the Royal Society, who were interested
in codes and ciphers as well as the study of nature. Like the infinite shelves
of books described in Borges’ story “The Library of Babel,” the device he
describes contained all possible sentences, both sensible and nonsensical:
Six Hours a-day the young Students were employed in
this Labour, and the Professor shewed me several Volumes in large Folio already
collected, of broken Sentences, which he intended to piece together, and out of
those rich Materials to give the World a compleat Body of all Arts and
Sciences; which however might be still improved, and much expedited, if the
Publick would raise a Fund for making and employing five hundred such Frames
in Lagado, and oblige the Managers to contribute in common their several
Collections.Every one knew how laborious
the usual Method is of attaining to Arts and Sciences; whereas by his Contrivance,
the most ignorant Person at a reasonable Charge, and with a little bodily
Labour, may write Books in Philosophy, Poetry, Politicks, Law, Mathematicks and
Theology, without the least Assistance from Genius or Study. He then led me to
the Frame, about the Sides whereof all his Pupils stood in Ranks. It was twenty
Foot Square, placed in the middle of the Room. The Superficies was composed of
several bits of Wood, about the bigness of a Dye, but some larger than others.
They were all linked together by slender Wires. These bits of Wood were covered
on every Square with Paper pasted on them, and on these Papers were written all
the Words of their Language, in their several Moods, Tenses, and Declensions,
but without any Order. The Professor then desired me to observe, for he was
going to set his Engine at Work. The Pupils at his Command took each of them
hold of an Iron Handle, whereof there were fourty fixed round the Edges of the
Frame, and giving them a sudden turn, the whole Disposition of the Words was entirely
changed. He then commanded six and thirty of the Lads to read the several Lines
softly as they appeared upon the Frame; and where they found three or four
Words together that might make part of a Sentence, they dictated to the four
remaining Boys who were Scribes. This Work was repeated three or four Times,
and at every turn the Engine was so contrived that the Words shifted into new
Places, as the Square bits of Wood moved upside down.
He assured me, that this Invention had employed all his
Thoughts from his Youth, that he had emptyed the whole Vocabulary into his
Frame, and made the strictest Computation of the general Proportion there is in
Books between the Numbers of Particles, Nouns, and Verbs, and other Parts of
Speech.[1]
Turing’s
Love Letter
Perhaps the first person to use an electronic computer to compose original
pieces of writing was Alan Turing. He wrote a love poem generator as a
joke in 1947. It used random numbers to choose nouns and adjectives to fill
some of the parts of a canned love letter[2]:
Darling Sweetheart,
You are my avid fellow feeling. My affection curiously clings to your
passionate wish. My liking yearns to your heart. You are my wistful sympathy:
my tender liking.
Yours beautifully
M.U.C.
Compared to the love letters of, say, Robert and Elizabeth
Browning, it comes up a little short. It is similar in structure to how the
utterances of fate were determined in divination rituals. The design is the
kaleidoscopic pattern:
- · A system of generating unpredictable output (in this case, a pseudorandom number generator).
- · Elements to be recombined which themselves have some aesthetic appeal. (The words such as sweetheart, wistful, or tender which are randomly chosen.)
- · A structure that imposes certain constraints on the results so that they will be interpreted as a sensible arrangement. (The fixed sentence grammar.)
Artists will protest that by “creative” we mean something
more than this. What more could be added to a machine besides a larger number
of elements and ways to be rearranged, and a more versatile and subtle
structure to put them in? I think that the answer lies in the ability to
recognize beauty or quality, in order to reject generated art that doesn’t meet
this standard, rather than simply constraining the possible creations. Research
into how to accomplish this is still in its infancy.
ELIZA
The first program designed for natural language conversation
was a simulation of a psychiatrist, known as Eliza. Eliza’s conversation used
the patient’s words in a superficial attempt to keep the conversation going on
a topic without contributing much of its own. For example:
Well, my boyfriend made me come here.
YOUR BOYFRIEND MADE YOU COME HERE
He says I'm depressed much of the time.
I AM SORRY TO HEAR YOU ARE DEPRESSED
It's true. I am unhappy
DO YOU THINK COMING HERE WILL HELP YOU NOT TO BE UNHAPPY
I need some help, that much seems certain.
Eliza is an attempt to automate (or perhaps parody) nondirective
Rogerian psychotherapy, a method developed in the 1940’s and 50’s by psychologist
Carl Rogers. Rogers recommended a technique he called “reflection,” in which a
therapist restates the patient’s concern to show empathy and understanding, and
to help the patient to find a way to solve his or her own problem. The key to
this method is that the doctor is not providing solutions to the problems; the
patient is providing both the problems and the solutions.
This helps us understand how meaning can be created by divination
or artistic machines. When a fortune teller sits down with a client, very
little actually comes from the system of manipulating signs. Instead, the
fortune teller provides a way for the subconscious mind of the client to
interpret a signal out of noise.
Similarly, our response to generated art is like finding
shapes in the clouds or Rorschach’s inkblots. The beauty and meaning come from
our attempt to find something we recognize in randomness. The machine itself
does not have actual experiences to draw on. But what it can do is form an
effective mirror where the viewer both provides, and is affected by, the
meaning.
The author of the Eliza program, Joseph Weizenbaum, stated in
an interview:
You can see Eliza using one basic method or, you could even
say, trick: Eliza relies on the fact that the human being interprets the
signals he perceives. He interprets these signals according to his needs and
his interests. He projects his own image of his partner, whether this is a
living human, conversing, or whether this is a living human being and a doll
interacting or whatever.
He doubted the possibility of a programmed machine ever being
able to actually mean the things it was saying:
No, that's impossible. The human being becomes a human,
because he is understood and treated as a human by other humans. And that's
where the deepest truths come from which nourish the human being - for example
trust: to trust another human. There are things, like for example a hand on
your shoulder: language is closely related to this and is learnt and developed
by being based on such experiences. The computer can't have these experiences.
So we return to the question of meaning.[3] Do
the words in a book have meaning, after the writer has written them and before
the reader has picked it up? Imagine finding a book in the library, and being
moved by what is written there. If the words that one finds meaningful got
there by some other process than being written by an author (say, by monkeys
pounding on typewriters who got really lucky), can we say that the meaning is somehow
false, not meaning at all because it wasn’t meant?
That doesn’t seem right. But Weizenbaum’s point too, seems like common sense.
Meaning can’t just pop up, like so many crocuses in the spring. For there to be
meaning, it seems like there has to be a mind.
It is simple to create a system that contains the fact “PARIS
is the CAPITAL of FRANCE.” The same system could also contain the phrase “PARIS
is the CAPTAL of THE MOON,” without protest. This is because it doesn’t
understand the words PARIS, CAPITAL, FRANCE, or THE MOON. But systems are being
developed[4]
that will contain the fact that capitals have to be of countries, that all
countries are on the earth, that one can’t have a city where no one lives, that
Paris is a city, that the moon is uninhabitable, and so on—millions upon
millions of facts and the logical means to connect them and derive new facts
from them. Such a system would balk at being told that Paris is the capital of
the moon, because it is inconsistent with the large body of facts it already
contains. In this limited sense, it can be said to “understand” what the
sentence means.
However, there is another sense of the word “understand” that
will be discussed in Chapter VI, where we “understand” when someone mentions a
particular sensory experience they have had, such as listening to music. This
kind of understanding cannot be
communicated through a network of relationships and definitions. Whenever
humans understand something, it is at the lowest level grounded in this kind of
direct understanding, direct experiencing, that can’t be broken down further. Part
of what I mean by THE MOON is what it feels like to be gazing up at it on a
cold October evening. I can only point to that experience, and if you’ve had
one similar, you can understand. If not, no amount of explaining is going to
communicate it to you.
For practical purposes this doesn’t make much difference, and
most AI researchers are mainly concerned about practical purposes. For artists,
though, it seems to matter a great deal. For some reason, we do care whether an
artist is being authentic. The idea of receiving love letters written by
someone who is not actually in love, but is incapable of feeling at all and is only
“going through the motions” is distasteful even if we’re sure they’ll keep up
the pretence.
In review, then, machines made to generate text all followed
a similar pattern: strict rules to guarantee grammatical correctness with a few
random elements. To the extent that the text they generated was meaningful, the
meaning originated in the creator of the machine or in the reader.
For all their flaws, though, these machines did generate new
text every time they were run. The machines in the next chapter, while
imitating many fascinating abilities, don’t rise to that standard. However,
they do illustrate the growing capability of machines to imitate other human
faculties needed for creative expression.
[1] Swift, Gulliver’s Travels
III:V
[2]Lavington, 1975 from Boden,
Mind as Machine p. 674. It would be
interesting to discover who Turing intended these letters for, given what is
now common knowledge about his sexual orientation.
[3] The study of meaning in
language is called semantics. The
phrase “semantick philosophy” was used in the 1600’s and 1700s to refer to the
study of divination systems. For example, in The British Apollo (Vol. III,
1708), the anonymous author writes “Bacon proposes this and several other sorts
of divination as parts of rational and useful knowledge. Whatever this
Semantick Philosophy was in former times…”
A better known reference is from John Spencer, A Discourse Concerning Prodigies, 1665.
[4] Doug Lenat’s CYC or the Commonsense Computing Initiative
at MIT are two prominent examples, though they will probably be surpassed by
other efforts soon. The Semantic Web is a related effort advocated by Tim
Berners-Lee, who invented the web. “Semantic” refers to meaning; the Semantic
Web is an effort to develop tools and practices that will allow this kind of
automated reasoning to take place across the internet.
