yamauchi@cs.rochester.edu (Brian Yamauchi) (11/02/90)
In article <3413@aipna.ed.ac.uk> cam@aipna.ed.ac.uk (Chris Malcolm) writes: In article <1990Oct31.001104.22908@ncsuvx.ncsu.edu> fostel@eos.ncsu.edu (Gary Fostel) writes: >Malcolm reveals the same chip-on-the-shoulder attitude when he asks about the >shortcommings of "a view of the scientific method so narrowly dominated >by the particular practices of a few sciences as to condemn those too >different to the status of non-sciences?" Well, first of all, it is not >restricted to the practises of a few sciences, but there are a few fields of >enquiry in which the methods happen to be "scientific". He begs the question >in his statement of it. But the real point is that not being a science is >not "condemning" anything. It just means it is not a science. Lawyers are >not troubled to be in a non-scientific field, nor are doctors, artists, >engineers and a great many other respectable people. What is so bad about >not being a science? Nothing. I'm not being chip-on-shoulder, it wouldn't upset me at all not to be a scientist, it just so happens that I think that AI is a science. Why? Because (unlike law or engineering) AI is trying to understand something, to add to human knowledge of the Universe. The things we make, and the programs we write, are experiments designed to teach us something. But AI is also trying to learn *how* to build systems that behave intelligently. This part of the field falls more into the tradition of engineering than science. However, AI does not have the (mathematical/quantitative) "flavor" of most traditional engineering fields. AI is also much more dynamic and more willing to experiement with completely new paradigms. In these ways, AI research is more similar to innovation than either science or engineering. Elaine Rich's definition of AI is "the study of how to make computers do things at which, at the moment, people are better." While this definition has some flaws, I think it reflects the degree to which AI is tied to innovation -- learning how to do new things and how to build new tools. In my experience, the AI research community is split into two motivational camps which are orthogonal to the ideological camps (logicists, connectionists, roboticists, etc). The first group wants to understand intelligence in the abstract. I would call the people in this group Cognitive Scientists. The second group wants to build intelligent systems. I would call the people in this group Intelligence Architects. Even though specific Scientists and Architects may use similar techniques, their goals are quite different. Scientists want to build intelligent systems so they can learn about intelligence. Architects want to learn about intelligence so that they can build intelligent systems. (Actually, there is also a third group whose members don't really care about intelligence, but just want to do interesting work and/or build useful systems.) >This has gotten too long again, but Malcolm asked me two specific questions >which I will address, namely do I believe: > > that AI is _properly_ a part of Computer Science [he continued] then > I'd be interested to hear why. For my part I think considering AI to be > a branch of CS is as silly as considering Astronomy to be a branch of > Optics. >The first seems to be a variation on the "When did I stop beating my wife" >classic. The realtive "size" and "scope" of astronomy and optics as the >question is posed is absurd and arguably insulting to astronomers and by >analogy, to Computer "Scientists". (Also not a science.) Well, I already knew that's how you felt about it, but I don't think the relative size and scope of the disciplines has much to do with the point of principle involved. You haven't answered my question, you have merely re-iterated your opinion. I agree that size and scope are irrelevant. It might be better to view CS and AI as broad fields with extensive overlap. Both also overlap with other fields -- CS with mathematics and computer engineering, AI with robotics, psychology, and philosophy. It's interesting that you use the example of Astronomy, because I view the relationship between Cognitive Science and Intelligence Architecture as analogous to the relationship between Astronomy and Space Exploration. The fields are related and support each other, but they have different goals and different criteria for success. Astronomical discoveries can be used in space exploration missions, and space missions can be used to further astronomical knowledge. The difference is whether the emphasis is on the learning or the doing -- the knowledge or the achievement. -- _______________________________________________________________________________ Brian Yamauchi University of Rochester yamauchi@cs.rochester.edu Computer Science Department _______________________________________________________________________________