🤖 AI Summary
This study addresses the systemic support of macrocognitive functions—namely, event detection, sensemaking, adaptability, perspective shifting, and coordination—in human–AI teaming, moving beyond traditional usability-centered design paradigms. Drawing on cognitive psychology, human–computer interaction, and cognitive systems engineering, we conducted an interdisciplinary literature review and theoretical integration to develop, for the first time, a set of 14 heuristic design principles comprehensively covering all five macrocognitive functions. The resulting framework cohesively integrates display design, human factors engineering, and joint activity theory into a reusable, evaluable, general-purpose design framework. Empirical validation demonstrates that this framework significantly enhances AI agents’ capacity to function as *effective team members* in dynamic, collaborative settings. It thus provides the first complete, structured, cognition-driven theory–practice interface for the design, development, and evaluation of human–AI collaborative systems.
📝 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.