Would You Trust a (Faulty) Robot? Effects of Error, Task Type and Personality on Human-Robot Cooperation and Trust

By Maha Salem, Gabriella Lakatos, Farshid Amirabdollahian, Kerstin Dautenhahn. IEEE/ACM International Conference on Human-Robot Interaction, 2015

647 citations recorded by the source corpus.

How do mistakes made by a robot affect its trustworthiness and acceptance in human-robot collaboration? We investigate how the perception of erroneous robot behavior may influence human interaction choices and the willingness to cooperate with the robot by following a number of itsunusual requests. For this purpose, we conducted an experiment in which participants interacted with a home companion robot in one of two experimental conditions: (1) the correct modeor (2) the faulty mode. Our findings reveal that, while significantly affecting subjective perceptions of the robot and assessments of its reliability and trustworthiness, the robot’s performance does not seem to substantially influence participants’ decisions to (not) comply with its requests. However, our results further suggest that the nature of the task requested by the robot, e.g. whether its effects are revocable as opposed to irrevocable, has a significant impact on participants’ willingness to follow its instructions.

Subfields: Artificial Intelligence, Safety Research, Social Psychology

View Paper: https://www.semanticscholar.org/paper/344b00021c1ff66cb0efdd2648dd735976e7d582

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Citations in the corpus

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development (2018, methodology): “…Salem et al., 2013; Bajones et al., 2016; Engelhardt and Hansson, 2017; Mirnig et al., 2017; Sarkar et al., 2017), reliability (Short et al., 2010; Salem et al., 2015), familiarity (Gompei and Umemuro, 2015), anthropomorphism (Lee et al., 2010; Salem et al., 2013, 2015; Lemaignan et al., 2015;…”
Human Trust in Artificial Intelligence: Review of Empirical Research (2020, background): “For instance, Salem, Lakatos, Amirabdollahian, and Dautenhahn (2015) found that people followed a human-like robot ’ s instructions even when they witnessed its erroneous behavior.”
Towards a Theory of Longitudinal Trust Calibration in Human–Robot Teams (2019, background): “Previous research on trust in HRTs has primarily focused on identifying initial trust states and potential determinants [9,53,126].”
A Systematic Review of Attitudes, Anxiety, Acceptance, and Trust Towards Social Robots (2020, background): “Trust has also been recognised as a factor that, at least in part, predicts not only the quality of HRI but also how willing people are to use social robots for certain tasks [28].”
Marketing robot services in hospitality and tourism: the role of anthropomorphism (2019, background): “For instance, extroversion and emotional stability may relate positively to anthropomorphiz-ing a robot (Salem, Lakatos, Amirabdollahian, & Dautenhahn, 2015) and therefore shape HRI.”
How People Explain Action (and Autonomous Intelligent Systems Should Too) (2017, background): “People sometimes over-trust artificial agents, such as when they comply with a faulty robot’s unusual requests (Salem et al. 2015) or follow the lead of a potentially dysfunctional robot (Robinette et al. 2016).”