Human-centered automation: A matter of agent design and cognitive function allocation

Abstract

This chapter presents an analytical framework that brings answers to and overcomes the "classical" debate on direct manipulation versus interface agents. Direct manipulation is always appropriate when the system to be controlled is simple. However, when users need to interact with complex systems, direct manipulation is also complex and requires a sufficient level of expertise. Users need to be trained, and in some cases deeply trained. They also need to be assisted to fulfill overall criteria such as safety, comfort or high performance. Artificial agents are developed to assist users in the control of complex systems. They are usually developed to simplify work, in reality they tend to change the nature of work. They do not remove training. Artificial agents are evolving very rapidly, and incrementally create new practices. An artificial agent is associated to a cognitive function. Cognitive function analysis enables human-centered design of artificial agents by providing answers to questions such as: Artificial agents for what? Why are artificial agents not accepted or usable by users? An example is provided, analyzed and evaluated. Current critical issues are discussed. © 2004 Springer Science + Business Media, Inc.