Collaborative Human-Automation Decision Making

The development of a comprehensive collaborative human–computer decision-making model is needed that demonstrates not only what decision-making functions should or could be assigned to humans or computers, but how many functions can best be served in a mutually supportive environment in which the human and computer collaborate to arrive at a solution superior to that which either would have come to independently. To this end, we present the human–automation collaboration taxonomy (HACT), which builds on previous research by expanding the Parasuraman information processing model [26.1], specifically the decision-making component. Instead of defining a simple level of automation for decision making, we deconstruct the process to include three distinct roles: the moderator, generator, and decider. We propose five levels of collaboration (LOCs) for each of these roles, which form a three-tuple that can be analyzed to evaluate system collaboration, and possibly identify areas for design intervention. A resource allocation mission planning case study is presented using this framework to illustrate the benefit for system designers.