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Published in U.S. 1 Newspaper on June 14, 2000. All rights

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Artificial IQ: Is it a Fair Test?

E-mail: MelindaSherwood@princetoninfo.com

Karin Verspoor and other computer scientists at

Intelligenesis in New York City are discovering that creating

artificial

intelligence is a little bit like child-rearing. There a team of

researchers

are raising "WebMind," a software program that will

"think"

in the same abstract, relational, and creative way that humans do.

Like a parent coaching a child, Verspoor, who directs natural language

engineering, tries not to program WebMind on what to "think,"

but to give it the tools essential to thought itself. "You can

hard-code a lot of knowledge but then you’re not giving it the tools

to find and learn new information," says Verspoor. With a true

artificial intelligence system, says Verspoor, "you can ask

questions

that can’t be answered just by spitting back an answer that you’ve

heard before, but are done by making connections, generalizing, the

kind of things that you and I take for granted."

Verspoor speaks on "A Distributed Architecture for Artificial

Intelligence," on Wednesday, June 21, at 6:30 p.m. at the

Association

for Women In Science at Princeton University’s Engineering Quad, Room

217. Call 732-235-5048.

A speaker of both Dutch and English, Verspoor has a unique

relationship

with language. She earned her BA in computer science at Rice

University,

Class of 1993, while simultaneously completing a degree in cognitive

science so she could incorporate elements of psychology, philosophy,

and linguistics into her work. She later earned a PhD in cognitive

science from the University of Edinburgh in Scotland.

Verspoor began working with Intelligenesis after a year-long residency

at the Microsoft Research Institute in Sidney, Australia, the

now-defunct

institute funded by Microsoft Australia. "The experience at the

research institute was great," says Verspoor, "because they

supported free research, no strings attached. We focused on natural

language generation problems, which is going from an underlying

representation

of meaning to a surface form, to a sentence or paragraph that conveys

that meaning."

Talking linguistics gets tricky, but if you can imagine how long it

takes to completely verse a person in the English language — from

birth to early adulthood, let’s say — you get an idea of how

difficult

it is to get a machine to understand a human language. One of the

major challenges for programmers is getting the computer to move from

concrete to abstract concepts. "If you’re interacting with a child

and point to a green cup and say `cup’ over and over again, they will

figure out it’s a cup," says Verspoor. "But eventually they

move to the abstract notion of a cup, that it doesn’t have to be a

green cup in order for it to be a cup."

Programmers at Intelligenesis are attempting to endow WebMind with

that kind of human reasoning. "You could teach it that a cup is

distinct from a glass, and that’s done in traditional artificial

intelligence

work," says Verspoor, "but there are two problems with that:

it’s actually hard to figure out all the important relationships,

and also it’s a lot of work to encode that by hand. Eventually you

hit a dead end unless you give the system the tools for learning

itself."

Once the concepts are in place, the next challenge for programmers

is getting the machine to translate those into language. "If you

have an abstract representation of a relationship, like you know that

a cat is similar to a lion," says Verspoor, "you still need

to work out how to basically use the grammatical constraints of the

language to produce a sentence."

Although still in its infancy, WebMind will be used for advanced

information

retrieval and numerical predictions that could change the way stocks

are traded. "It could predict whether the stock market is going

to go up or down on more than just numerical modeling — it will

look at what has happened in the past, psychological factors,"

says Verspoor.

Intelligenesis signed its first commercial partnership on June 7 with

NetCurrents, a company that analyzes communications from a universe

of targeted Internet locations and provides real time information

to its clients. The company chose to add WebMind’s artificial

intelligence

functionality to its AgencyFacts Internet monitoring and analysis

service, which serves public and investor relations agencies with

information on most talked about topics, online sentiment, most active

posters, real-time percentage breakdown of volume on the most active

message boards, and the 10 most recent messages within minutes of

posting.

Even though WebMind will eventually think in much the same way humans

do, says Verspoor, its capacity will far exceed that of humans.

"It

could keep track of every single word in a newspaper, which humans

obviously don’t do, since we abstract the knowledge and combine it

with other knowledge. It also has access to a lot more techniques

for finding new knowledge than any human. It can be an expert in

mathematical

modeling, physics, and linguistics because it’s being programmed by

people who are experts in those areas."

But the problem with artificial intelligence, says Verspoor, is every

time you think you’ve achieved "intelligence" somebody else

redefines it. "It’s called the moving frontier," she says.

One of the first scientists to prophesy that computers would one day

think, Alan Turing, defined an "intelligent" machine as one

that could not be deciphered from a human in an interrogation.

Computer

experts today consider that definition naive. "It’s really not

a good test for an intelligent system because it doesn’t require the

system to learn," says Verspoor. "It just requires the system

to be able to simulate human conversations."

By those standards, people are already using artificial intelligence

today, says Verspoor. Speech-recognition systems, for example.

"Obviously

the technology is going to improve with time," she says.

"Little

by little, we’ll see more artificial intelligence coming into the

applications we’re using. But at some level, people always want to

see themselves as more intelligent than a machine."


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