The (Fe)male Robot: How Robot Body Shape Impacts First Impressions and Trust Towards Robots

Bernotat, Jasmin; Eyssel, Friederike Anne; Sachse, Janik

doi:10.1007/s12369-019-00562-7

Cited by 76 publications

(72 citation statements)

References 42 publications

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“…Cognitive trust is measured by assessing the robot's performance and affective trust by assessing a robot's motives. Prominent factors that influence cognitive trust in a robot are its task performance and characteristics (Hancock et al, 2011;Bernotat et al, 2019), the timing and magnitude of errors (Rossi et al, 2017a;Rossi et al, 2017b) and even physical appearance such as a genderspecific body shape (Bernotat et al, 2019). In contrast to this however stands the "uncanny valley" phenomenon: when a robot exhibits aesthetic characteristics too similar to a human, this can negatively impact trust.…”

Section: Trust and The Investment Gamementioning

confidence: 99%

An Immersive Investment Game to Study Human-Robot Trust

et al. 2021

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As robots become more advanced and capable, developing trust is an important factor of human-robot interaction and cooperation. However, as multiple environmental and social factors can influence trust, it is important to develop more elaborate scenarios and methods to measure human-robot trust. A widely used measurement of trust in social science is the investment game. In this study, we propose a scaled-up, immersive, science fiction Human-Robot Interaction (HRI) scenario for intrinsic motivation on human-robot collaboration, built upon the investment game and aimed at adapting the investment game for human-robot trust. For this purpose, we utilize two Neuro-Inspired COmpanion (NICO) - robots and a projected scenery. We investigate the applicability of our space mission experiment design to measure trust and the impact of non-verbal communication. We observe a correlation of 0.43 (p=0.02) between self-assessed trust and trust measured from the game, and a positive impact of non-verbal communication on trust (p=0.0008) and robot perception for anthropomorphism (p=0.007) and animacy (p=0.00002). We conclude that our scenario is an appropriate method to measure trust in human-robot interaction and also to study how non-verbal communication influences a human’s trust in robots.

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Section: Trust and The Investment Gamementioning

confidence: 99%

An Immersive Investment Game to Study Human-Robot Trust

et al. 2021

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“…While a robot's design can prime the user to adopt a certain level of trust in it, the design's efficacy is often dependent on the context [39] and individual differences among human users [40,41]. As such, design alone may not be sufficient to induce the appropriate level of trust.…”

Section: Gaining Maintaining and Calibrating Trustmentioning

confidence: 99%

Trust in Robots: Challenges and Opportunities

2020

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Purpose of Review To assess the state-of-the-art in research on trust in robots and to examine if recent methodological advances can aid in the development of trustworthy robots. Recent Findings While traditional work in trustworthy robotics has focused on studying the antecedents and consequences of trust in robots, recent work has gravitated towards the development of strategies for robots to actively gain, calibrate, and maintain the human user's trust. Among these works, there is emphasis on endowing robotic agents with reasoning capabilities (e.g., via probabilistic modeling). Summary The state-of-the-art in trust research provides roboticists with a large trove of tools to develop trustworthy robots. However, challenges remain when it comes to trust in real-world human-robot interaction (HRI) settings: there exist outstanding issues in trust measurement, guarantees on robot behavior (e.g., with respect to user privacy), and handling rich multidimensional data. We examine how recent advances in psychometrics, trustworthy systems, robot-ethics, and deep learning can provide resolution to each of these issues. In conclusion, we are of the opinion that these methodological advances could pave the way for the creation of truly autonomous, trustworthy social robots.

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“…Whereas human-human trust has been extensively studied, humanrobot trust poses new and complex research challenges. Prominent factors that influence trust in a robot are robot performance and characteristics [6,23], and the timing and magnitude of robot errors [42,43]. When it comes to trust, the prediction and predictability of behaviour are fundamental [52].…”

Section: Trust and The Investment Gamementioning

confidence: 99%

“…For this purpose, we use the Godspeed questionnaire [3] except for the Perceived Safety category since the participant did not have to physically interact with the robots and kept their distance throughout the experiment. The post-study questionnaire also asks the participant to rate the trustworthiness [6] and performance of each robot and choose which robot they preferred as an assistant, as well as provide feedback about shortcomings, immersion, and their overall experience during the experiment.…”

Section: Protocol and Game Scenesmentioning

confidence: 99%

Exploring Human-Robot Trust Through the Investment Game

Arts

Zörner

Bhatia

et al. 2020

Proceedings of the 8th International Conference on Human-Agent Interaction

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As robots become more advanced and capable, developing trust is an important factor of human-robot interaction and cooperation. However, as multiple environmental and social factors can influence trust, it is important to develop more elaborate scenarios and methods to measure human-robot trust. A widely used measurement of trust in social science is the investment game. In this study, we propose a scaled-up, immersive, science fiction Human-Robot Interaction (HRI) scenario for intrinsic motivation on human-robot collaboration, built upon the investment game and aimed at adapting the investment game for human-robot trust. For this purpose, we utilise two Neuro-Inspired Companion (NICO)-robots and a projected scenery. We investigate the applicability of our space mission experiment design to measure trust and the impact of nonverbal communication. We observe a correlation of 0.43 (p = 0.02) between self-assessed trust and trust measured from the game and a positive impact of non-verbal communication on trust (p = 0.0008) and robot perception for anthropomorphism (p = 0.007) and animacy (p = 0.00002). We conclude that our scenario is an appropriate method to measure trust in human-robot interaction and also to study how non-verbal communication influences a human's trust in robots.

show abstract

The (Fe)male Robot: How Robot Body Shape Impacts First Impressions and Trust Towards Robots

Cited by 76 publications

References 42 publications

An Immersive Investment Game to Study Human-Robot Trust

An Immersive Investment Game to Study Human-Robot Trust

Trust in Robots: Challenges and Opportunities

Exploring Human-Robot Trust Through the Investment Game

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