HCAIROSep 11, 2019

Trust and Cognitive Load During Human-Robot Interaction

arXiv:1909.05160v13 citations
Originality Synthesis-oriented
AI Analysis

This addresses trust dynamics in human-robot interaction for applications like teamwork, but it is incremental as it builds on existing research with specific experimental conditions.

The study investigated how cognitive load, trust, and anthropomorphism interact during human-robot collaboration in a game, finding an inverse relationship where increased cognitive load decreased trust, and that robot type and error rate influenced trust perceptions.

This paper presents an exploratory study to understand the relationship between a humans' cognitive load, trust, and anthropomorphism during human-robot interaction. To understand the relationship, we created a \say{Matching the Pair} game that participants could play collaboratively with one of two robot types, Husky or Pepper. The goal was to understand if humans would trust the robot as a teammate while being in the game-playing situation that demanded a high level of cognitive load. Using a humanoid vs. a technical robot, we also investigated the impact of physical anthropomorphism and we furthermore tested the impact of robot error rate on subsequent judgments and behavior. Our results showed that there was an inversely proportional relationship between trust and cognitive load, suggesting that as the amount of cognitive load increased in the participants, their ratings of trust decreased. We also found a triple interaction impact between robot-type, error-rate and participant's ratings of trust. We found that participants perceived Pepper to be more trustworthy in comparison with the Husky robot after playing the game with both robots under high error-rate condition. On the contrary, Husky was perceived as more trustworthy than Pepper when it was depicted as featuring a low error-rate. Our results are interesting and call further investigation of the impact of physical anthropomorphism in combination with variable error-rates of the robot.

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