Relay-Version: version B 2.10 5/3/83; site utzoo.UUCP Path: utzoo!mnetor!seismo!rutgers!ucla-cs!zen!ucbvax!SDCSVAX.UCSD.EDU!norman%ics From: norman%ics@SDCSVAX.UCSD.EDU (Donald A. Norman) Newsgroups: comp.ai.digest Subject: Why AI is not a science Message-ID: <8707031429.AA11064@sunl.ICS> Date: Fri, 3-Jul-87 10:29:41 EDT Article-I.D.: sunl.8707031429.AA11064 Posted: Fri Jul 3 10:29:41 1987 Date-Received: Tue, 7-Jul-87 01:28:52 EDT Sender: usenet@ucbvax.BERKELEY.EDU Distribution: world Organization: Donald A. Norman, UCSD Institute for Cognitive Science Lines: 75 Approved: ailist@stripe.sri.com A private message to me in response to my recent AI List posting, coupled with general observations lead me to realize why so many of us otherwise friendly folks in the sciences that neighbor AI can be so frustrated with AI's casual attitude toward theory: AI is not a science and its practitioners are woefuly untutored in scientific method. At the recent MIT conference on Foundations of AI, Nils Nilsson stated that AI was not a science, that it had no empirical content, nor claims to emperical content, that it said nothing of any emperical value. AI, stated Nilsson, was engineering. No more, no less. (And with that statement he left to catch an airplane, stopping further discussion.) I objected to the statement, but now that I consider it more deeply, I believe it to be correct and to reflect the dissatisfaction people like me (i.e., "real scientists") feel with AI. The problem is that most folks in AI think they are scientists and think they have the competence to pronounce scientific theories about almost any topic, but especially about psychology, neuroscience, or language. Note that perfectly sensible dsciplines such as mathematics and philosophy are also not sciences, at least not in the normal intrerpretation of that word. It is no crime not to be a science. The crime is to think you are one when you aren't. AI worries a lot about methods and techniques, with many books and articles devoted to these issues. But by methods and techniques I mean such topics as the representation of knowledge, logic, programming, control structures, etc. None of this method includes anything about content. And there is the flaw: nobody in the field of Artificial Intelligence speaks of what it means to study intelligence, of what scientific methods are appropriate, what emprical methods are relevant, what theories mean, and how they are to be tested. All the other sciences worry a lot about these issues, about methodology, about the meaning of theory and what the appropriate data collection methods might be. AI is not a science in this sense of the word. Read any standard text on AI: Nilsson or Winston or Rich or even the multi-volumned handbook. Nothing on what it means to test a theory, to compare it with others, nothing on what constitutes evidence, or with how to conduct experiments. Look at any science and you will find lots of books on experimental method, on the evaluation of theory. That is why statistics are so important in psychology or biology or physics, or why counterexamples are so important in linguistics. Not a word on these issues in AI. The result is that practitioners of AI have no experience in the complexity of experimental data, no understanding of scientific method. They feel content to argue their points through rhetoric, example, and the demonstration of programs that mimic behavior thought to be relevant. Formal proof methods are used to describe the formal power of systems, but this rigor in the mathematical analysis is not matched by any similar rigor of theoretical analysis and evaluation for the content. This is why other sciences think that folks in AI are off-the-wall, uneducated in scientific methodology (the truth is that they are), and completely incompetent at the doing of science, no matter how brilliant at the development of mathematics of representation or formal programming methods. AI will contribute to the A, but will not contribute to the I unless and until it becomes a science and develops an appreciation for the experimental methods of science. AI might very well develop its own methods -- I am not trying to argue that existing methods of existing sciences are necessarily appropriate -- but at the moment, there is only clever argumentation and proof through made-up example (the technical expression for this is "thought experiment" or "gadanken experiment"). Gedanken experiments are not accepted methods in science: they are simply suggestive for a source of ideas, not evidence at the end. don norman Donald A. Norman Institute for Cognitive Science C-015 University of California, San Diego La Jolla, California 92093 norman@nprdc.arpa {decvax,ucbvax,ihnp4}!sdcsvax!ics!norman norman@sdics.ucsd.edu norman%sdics.ucsd.edu@RELAY.CS.NET