Enrico Coiera1. 1. Centre for Health Informatics, University of New South Wales, Sydney, NSW 2055, Australia. ewc@pobox.com
Abstract
OBJECTIVE: This paper presents a framework for the design of interactions between human and computational agents working in organisations, mediation by technological systems. DESIGN: The design of interactions within an organisation is viewed from the point of view, not of the technology mediating the new interaction, but of the human and computational agents who interact with each other. RESULTS: Understanding the limits to individual agent resources permits an analysis of the impact that a new interaction will have in a given setting. When we look beyond simple interaction settings, we can use the notion of interaction equilibria to predict the impact of new information and communication technologies within an organisation. Economic supply and demand curves, for example, may allow us to make both qualitative and quantitative predictions about technological adoption of communication systems. CONCLUSION: Rather than focusing solely on characteristics of individual technologies, or psychological and social issues, these can be combined to explain the overall decisions that individuals make when using technologies. Without necessarily understanding all the local decision criteria used by any individual, we can make robust predictions about how a group as a whole will interact.
OBJECTIVE: This paper presents a framework for the design of interactions between human and computational agents working in organisations, mediation by technological systems. DESIGN: The design of interactions within an organisation is viewed from the point of view, not of the technology mediating the new interaction, but of the human and computational agents who interact with each other. RESULTS: Understanding the limits to individual agent resources permits an analysis of the impact that a new interaction will have in a given setting. When we look beyond simple interaction settings, we can use the notion of interaction equilibria to predict the impact of new information and communication technologies within an organisation. Economic supply and demand curves, for example, may allow us to make both qualitative and quantitative predictions about technological adoption of communication systems. CONCLUSION: Rather than focusing solely on characteristics of individual technologies, or psychological and social issues, these can be combined to explain the overall decisions that individuals make when using technologies. Without necessarily understanding all the local decision criteria used by any individual, we can make robust predictions about how a group as a whole will interact.
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