back 50 years—in fact to the very beginning of computing—Turing was around to give us a vision of artificial intelligence and what it would be, beautifully explicated in the play about Turing's life, Breaking the Code.

Raj Reddy published a paper in the May 1996 Communications of the ACM, his Turing Award address, called "To Dream the Possible Dream." I, too, share that possible dream. However, I feel like the character in the William Steig cartoon who is tumbling through space saying, "I hope to find out what it is all about before it is out."

There is a kind of Edisonian analogue to this. Yes, we have invented the light bulb, and we have given people plans to build the generators. We have given them tools for constructing the generators. They have gone out and hand-crafted a few generators. There is one lamppost working here, or lights on one city block are working over there. A few places are illuminated, but most of the world is still dark. Yet the dream is to light up the world! Edison, of course, invented an electric company. So the vision is to find out what it is we must do—and I am going to tell you what I think it is—and then go out and build that electric company.

What we learned over the past 25 years is that the driver of the power of intelligent systems is the knowledge the systems have about their universe of discourse, not the sophistication of the reasoning process the systems employ. We have put together tiny amounts of knowledge in very narrow, specialized areas in programs called expert systems. These are the individual lampposts or, at most, the city block. What we need built is a large, distributed knowledge base. The way to build it is the way the data space of the World Wide Web came about—a large number of individuals contributing their data to the nodes of the Web. In the case I am talking about, people will be contributing their knowledge in machine-usable form. The knowledge would be presented in a neutral and general way—a way of building knowledge bases so they are reusable and extendible—so that the knowledge can be used in many different applications. A lot of basic work has been done to enable this kind of infrastructure growth. I think we just need the will to go down that road.


JEROME GLENN: As far as being timid about talking about the future, didn't we all get into computers because we wanted to focus global intelligence on the most difficult problems to solve? Things that we could not do alone? Are we going to create a global interface between human brains and problems and machines? Isn't that the direction? So what is this fear of talking about the future?

PETER FREEMAN: I see a fair amount of confusion between the development of products or technology and the development of concepts or understanding. Several of you touched on this in your comments about what goes on, or should go on, in university-based research. I quite agree that many of us in universities are too focused on the short term, but ultimately, if we are to get to that next generation of products and technology, we have to have some new concepts.

I would point out just one in an area that several of you identified, software engineering, which I agree is almost devoid of ideas. There are a few people—Mary Shaw is one of them—who are trying to develop ways to express the architecture of software systems. Without that kind of architectural representation and description, we will never be able to do the kinds of things that Edward Feigenbaum was asking about, for example.

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