Plans and Situated Actions: The Problem of Human-Machine Communication

This thesis considers two alternative views of purposeful action and shared understanding. The first, adopted by researchers in Cognitive Science, views the organization and significance of action as derived from plans, which are prerequisite to and prescribe action at whatever level of detail one might imagine. Mutual intelligibility on this view is a matter of the recognizability of plans, due to common conventions for the expression of intent, and common knowledge about typical situations and appropriate actions. The second view, drawn from recent work in social science, treats plans as derivative from situated action. Situated action as such comprises necessarily ad hoc responses to the actions of others and to the contingencies of particular situations. Rather than depend upon the reliable recognition of intent, successful interaction consists in the collaborative production of intelligibility through mutual access to situation resources, and through the detection, repair or exploitation of differences in understanding. As common sense formulations designed to accomodate the unforseeable contingences of situated action, plans are inherently vague. Researchers interested in machine intelligence attempt to remedy the vagueness of plans, to make them the basis for artifacts intended to embody intelligent behavior, including the ability to interact with their human users. The idea that computational artifacts might interact with their users is supported by their reactive, linguistic, and internally opaque properties. Those properties suggest the possibility that computers might 'explain themselves: thereby providing a solution to the problem of conveying the designer's purposes to the user, and a means of establishing the intelligence of the artifact itself. I examine the problem of human-machine communication through a case study of people using a machine designed on the planning model, and intended to be intelligent and interactive. A conversation analysis of “interactions” between users and the machine reveals that the machine's insensitivity to particular circumstances is a central design resource, and a fundamental limitation. I conclude that problems in Cognitive Science's theorizing about purposeful action as a basis for machine intelligence are due to the project of substituting plans for actions, and representations of the situation of action, for action's actual circumstances.