Artificial Trust in Mutually Adaptive Human-Machine Teams

Proceedings of the AAAI Symposium Series, vol. 4, pp. 18–23

Abstract

As machines' autonomy increases, their capacity to learn and adapt to humans in collaborative scenarios increases too. In particular, machines can use artificial trust (AT) to make decisions, such as task and role allocation/selection. However, the outcome of such decisions and the way these are communicated can affect the human's trust, which in turn affects how the human collaborates too. With the goal of maintaining mutual appropriate trust between the human and the machine in mind, we reflect on the requirements for having an AT-based decision-making model on an artificial teammate. Furthermore, we propose a user study to investigate the role of task-based willingness (e.g. human preferences on tasks) and its communication in AT-based decision-making.

Authors 5

1. Carolina Centeio Jorge

   University of Michigan · Delft University of Technology

   Affiliation as printed

   Delft University of Technology University of Michigan

2. Ewart J. de Visser

   United States Air Force Academy

   Affiliation as printed

   U.S. Air Force Academy

3. Myrthe Lotte Tielman

   Delft University of Technology

   Affiliation as printed

   Delft University of Technology

4. Catholijn M. Jonker Aachen

   Leiden University · Delft University of Technology

   Affiliation as printed

   Delft University of Technology University of Leiden

5. Lionel Robert

   University of Michigan

   Affiliation as printed

   University of Michigan