Joint Activity Design Heuristics for Enhancing Human-Machine Collaboration

TL;DR

This paper introduces a set of fourteen heuristics to guide the design and evaluation of technologies that facilitate effective joint activities between humans and machines, emphasizing coordination and cognitive support.

Contribution

It synthesizes heuristics from diverse fields to improve how technologies support interdependent human-machine teamwork.

Findings

Fourteen heuristics for joint activity design.

Heuristics support key macrocognitive functions.

Guidelines enhance human-machine collaboration effectiveness.

Abstract

Joint activity describes when more than one agent (human or machine) contributes to the completion of a task or activity. Designing for joint activity focuses on explicitly supporting the interdependencies between agents necessary for effective coordination among agents engaged in the joint activity. This builds and expands upon designing for usability to further address how technologies can be designed to act as effective team players. Effective joint activity requires supporting, at minimum, five primary macrocognitive functions within teams: Event Detection, Sensemaking, Adaptability, Perspective-Shifting, and Coordination. Supporting these functions is equally as important as making technologies usable. We synthesized fourteen heuristics from relevant literature including display design, human factors, cognitive systems engineering, cognitive psychology, and computer science to aid the design, development, and evaluation of technologies that support joint human-machine activity.