Kathleen R. McKeown
In the past several years, it has become increasingly apparent that there is strong disagreement between researchers within and outside of AI on how to build systems for man-machine communication. Within AI, and specifically within natural language, researchers have noted that human speakers and hearers draw on their knowledge about each other when communicating. This knowledge is used both in understanding, and responding to, a speaker’s utterances. User models are a means for representing various types of information about speakers and hearers so that systems are able to reason about their users when interpreting input and producing responses. While there is disagreement in the AI community about the form of user model that should be used, there is an implicit assumption that some form of knowledge about users is essential for successful man-machine communication.