“I Know You’re Capable, But Are You Willing?”: Allocating Tasks in Human-Machine Teams

In human–machine teams, task allocation algorithms typically prioritize competence and other performance-related factors, overlooking human willingness to perform specific tasks. A recent framework proposed incorporating both competence and willingness into task allocation, but its effects on teamwork outcomes remain untested. This paper investigates the impact of willingness-based task allocation in a simulated search and rescue (SAR) setting. We conducted a 2x2 user study (N=72) in a 2D grid-world SAR scenario, where human participants collaborated with two virtual robots, which either used a willingness-based or a balanced task allocation strategy. Half the participants were able to change the task allocation, prior to the start of the mission. Participants preferred robots and plans that accounted for their preferences, yet willingness-based allocation did not significantly influence trust in the robot or perceived team fluency, as these remained high throughout. Moreover, allowing changes to task allocation improved human performance. Our findings also suggest that the benefits of incorporating willingness may be context-dependent, with greater potential in lower-stakes tasks and longer-term teams.