Dataset Information

Robot leadership-Investigating human perceptions and reactions towards social robots showing leadership behaviors.

ABSTRACT: Human-robot interaction research has shown that social robots can interact with humans in complex social situations and display leadership-related behaviors. Therefore, social robots could be able to take on leadership roles. The aim of our study was to investigate human followers' perceptions and reactions towards robot leadership behavior, and differences based on the robot's displayed leadership style. We implemented a robot to show either a transformational or a transactional leadership style in its speech and its movements. We presented the robot to university and executive MBA students (N = 29) and subsequently conducted semi-structured interviews and group discussions. The results of explorative coding indicated that participants differed in their perceptions and reactions based on the robot's leadership style and based on their assumptions about robots in general. We observed that participants quickly imagined either a utopia or worried about a dystopia, depending on the robot's leadership style and their assumptions, and that a subsequent reflection led to more nuanced views. We discuss the implications and recommendations for human-robot interaction and leadership research.

SUBMITTER: Cichor JE

PROVIDER: S-EPMC9934409 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Robot leadership-Investigating human perceptions and reactions towards social robots showing leadership behaviors.

Cichor Jakub Edward JE Hubner-Benz Sylvia S Benz Tobias T Emmerling Franziska F Peus Claudia C

PloS one 20230216 2

Human-robot interaction research has shown that social robots can interact with humans in complex social situations and display leadership-related behaviors. Therefore, social robots could be able to take on leadership roles. The aim of our study was to investigate human followers' perceptions and reactions towards robot leadership behavior, and differences based on the robot's displayed leadership style. We implemented a robot to show either a transformational or a transactional leadership styl ...[more]

PMID: 36795649

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Project description:IntroductionRobots are being introduced into increasingly social environments. As these robots become more ingrained in social spaces, they will have to abide by the social norms that guide human interactions. At times, however, robots will violate norms and perhaps even deceive their human interaction partners. This study provides some of the first evidence for how people perceive and evaluate robot deception, especially three types of deception behaviors theorized in the technology ethics literature: External state deception (cues that intentionally misrepresent or omit details from the external world: e.g., lying), Hidden state deception (cues designed to conceal or obscure the presence of a capacity or internal state the robot possesses), and Superficial state deception (cues that suggest a robot has some capacity or internal state that it lacks).MethodsParticipants (N = 498) were assigned to read one of three vignettes, each corresponding to one of the deceptive behavior types. Participants provided responses to qualitative and quantitative measures, which examined to what degree people approved of the behaviors, perceived them to be deceptive, found them to be justified, and believed that other agents were involved in the robots' deceptive behavior.ResultsParticipants rated hidden state deception as the most deceptive and approved of it the least among the three deception types. They considered external state and superficial state deception behaviors to be comparably deceptive; but while external state deception was generally approved, superficial state deception was not. Participants in the hidden state condition often implicated agents other than the robot in the deception.ConclusionThis study provides some of the first evidence for how people perceive and evaluate the deceptiveness of robot deception behavior types. This study found that people people distinguish among the three types of deception behaviors and see them as differently deceptive and approve of them differently. They also see at least the hidden state deception as stemming more from the designers than the robot itself.

Project description:BackgroundFor robots to be effectively used in health applications, they need to display appropriate social behaviors. A fundamental requirement in all social interactions is the ability to engage, maintain, and demonstrate attention. Attentional behaviors include leaning forward, self-disclosure, and changes in voice pitch.ObjectiveThis study aimed to examine the effect of robot attentional behaviors on user perceptions and behaviors in a simulated health care interaction.MethodsA parallel randomized controlled trial with a 1:1:1:1 allocation ratio was conducted. We randomized participants to 1 of 4 experimental conditions before engaging in a scripted face-to-face interaction with a fully automated medical receptionist robot. Experimental conditions included a self-disclosure condition, voice pitch change condition, forward lean condition, and neutral condition. Participants completed paper-based postinteraction measures relating to engagement, perceived robot attention, and perceived robot empathy. We video recorded interactions and coded for participant attentional behaviors.ResultsA total of 181 participants were recruited from the University of Auckland. Participants who interacted with the robot in the forward lean and self-disclosure conditions found the robot to be significantly more stimulating than those who interacted with the robot in the voice pitch or neutral conditions (P=.03). Participants in the forward lean, self-disclosure, and neutral conditions found the robot to be significantly more interesting than those in the voice pitch condition (P<.001). Participants in the forward lean and self-disclosure conditions spent significantly more time looking at the robot than participants in the neutral condition (P<.001). Significantly, more participants in the self-disclosure condition laughed during the interaction (P=.01), whereas significantly more participants in the forward lean condition leant toward the robot during the interaction (P<.001).ConclusionsThe use of self-disclosure and forward lean by a health care robot can increase human engagement and attentional behaviors. Voice pitch changes did not increase attention or engagement. The small effects with regard to participant perceptions are potentially because of the limitations in self-report measures or a lack of comparison for most participants who had never interacted with a robot before. Further research could explore the use of self-disclosure and forward lean using a within-subjects design and in real health care settings.

Dataset Information

Robot leadership-Investigating human perceptions and reactions towards social robots showing leadership behaviors.

Publications

Robot leadership-Investigating human perceptions and reactions towards social robots showing leadership behaviors.

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