Collaborative Human–Automation Decision Making

Abstract

The developmentof a comprehensive collaborative human–computer decision-making model is needed that demonstrates not only what decision-makingfunctions should or could be assigned to humans or computers, but how many functions can best be served in a mutually supportiveenvironment in which the human and computer collaborate to arrive at a solution superior to that which either would have cometo independently. To this end, we present thehuman–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 deconstructthe process to include three distinct roles: themoderator, generator, and decider. We propose five levels of collaboration (LOCs) for each of these roles, which form a three-tuplethat can be analyzed to evaluate system collaboration, and possibly identify areas for design intervention. A resource allocationmission planning case study is presented using this framework to illustrate the benefit for system designers.