The existing work on task assignment of human-AI cooperation did not consider the differences between individual team members regarding their capabilities, leading to sub-optimal task completion results. In this work, we propose a capability-aware shared mental model (CASMM) with the components of task grouping and negotiation, which utilize tuples to break down tasks into sets of scenarios relating to difficulties and then dynamically merge the task grouping ideas raised by human and AI through negotiation. We implement a prototype system and a 3-phase user study for the proof of concept via an image labeling task. The result shows building CASMM boosts the accuracy and time efficiency significantly through forming the task assignment close to real capabilities within few iterations. It helps users better understand the capability of AI and themselves. Our method has the potential to generalize to other scenarios such as medical diagnoses and automatic driving in facilitating better human-AI cooperation.
https://doi.org/10.1145/3544548.3580983
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)