# Joint Activity Design Heuristics for Enhancing Human-Machine Collaboration

arXiv: https://arxiv.org/abs/2512.08036 · HTML: https://mlsanity.com/paper/2512.08036/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 73 references that are in the map.
- First posted on arXiv 8 Dec 2025.

## Builds on (most cited first, 1 of 1)

- [Metrics for Explainable AI: Challenges and Prospects](https://mlsanity.com/paper/1812.04608/) (2018)

## Abstract (arXiv)

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.