Artificial intelligence and other approaches to speech understanding: reflections on methodology

This paper characterizes the methodology of Artificial Intelligence by looking at research in speech understanding, a field where AI approaches contrast starkly with the alternatives, particularly engineering approaches. Four values of AI stand out as influential: ambitious goals, introspective plausibility, computational elegance, and wide significance. The paper also discusses the utility and larger significance of these values. 1 Introduction AI is often defined in terms of the problems it studies. But in fact, AI is not the study of intelligent behavior etc., it is a way to study it. This is evident from the way AI is done in practice. This paper illustrates this by contrasting AI and alternative approaches to speech understanding. By so doing it brings out some key characteristics of AI methodology. This paper is primarily written for a general AI audience interested in methodological issues, complementing previous work (Cohen 1991; Brooks 1991a). It is also written for any AI re...