Trust Transfer in Robots between Task Environments

Theresa Law, Meia Chita-Tegmark, Matthias Scheutz

Abstract: Trust and capability transfer between tasks and environments is common in human-human interactions. For human-robot interactions it is unclear how a robot’s performance of a task in one environment affects humans predictions about the robot’s performance of another related or unrelated task in a different environment. When making assessments about a robot’s task capabilities, three main sources of information are pertinent: the human’s “default mental model” of robots, the robot’s appearance, and the robot’s performance. We hypothesized that past task performance would be the most salient information source, and that participants who saw the robot perform tasks in one environment would transfer their assumptions about the robot’s capability to a new environment with new tasks. However, the results of our first study did not support this hypothesis. We then performed a second study to exclude the possibility that because the robot worked well in the first environment, it did not supply any salient, different information from the participants’ default mental model of robots (that robots are functional, etc.). If this hypothesis was correct, a faulty robot in the first environment would be rated significantly lower at the tasks in the second environment. However, the results did not support the second hypothesis either. We then conducted a third study investigating whether the tasks themselves or the environment had a stronger effect on trust assessments. The results showed that because individual judgments varied dramatically no systematic trust and task transfer result can be obtained. The upshot for HRI is that trust and task transfer are solely dependent on the individual’s background and judgment rather than on task or environmental properties.