A Meta-Analysis of Human Personality and Robot Acceptance in Human-Robot Interaction

Esterwood, Connor; Essenmacher, Kyle; Zeng, Fanpan; Robert, Lionel

doi:10.2139/ssrn.3768022

Cited by 12 publications

(16 citation statements)

References 61 publications

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“…2021) had sample sizes lower than 20. At the same time, the meta-analyses reported here show that effect sizes in HRI user studies seem to be rather small to moderate in most cases (Leichtmann and Nitsch, 2020a;Esterwood et al, 2021;Hancock et al, 2021;Roesler et al, 2021;Stower et al, 2021). Another hint for expecting rather low effect sizes is that a large portion of HRI user studies examined factors including anthropomorphism, attitudes, personality, gender, and others-topics that have been studied in context of the social sciences and are known to have rather small effect sizes (Richard et al, 2003).…”

Section: Meta-analyses In Hri Show Many Issuesmentioning

confidence: 53%

“…Therefore, a considerable proportion of HRI studies likely has only low predictive power, reports overestimated effect sizes, and has high probability of finding false-positive results. Another hint for a biased literature was also found in a funnel plot analysis by Esterwood et al (2021) .…”

Section: Confidence In Hri Researchmentioning

confidence: 71%

“…Taxonomies have been excluded from this analysis. In total, eight meta-analyses had been used to identify patterns of concern in the literature: A meta-analysis by 1) Leichtmann and Nitsch (2020a) on personal space in HRI with a total of k = 27 studies including N = 1,299 participants, by 2) Stower et al (2021) on trust in child-robot interaction including k = 20 studies with N = 977, by 3) Ötting et al (2020) on the effects of design features on HRI at work using k = 81 studies with N = 2,245, by 4) Esterwood et al (2021) on personality effects in HRI with k = 26 studies and N = 1,611, by 5) Roesler et al (2021) on anthropomorphism in HRI with k = 78 studies and N = 5,973, by 6) Hancock et al (2021) on trust in HRI using k = 45 studies, by 7) Yuan et al (2021) on the effect of robot-assisted cognitive training including k = 53 studies with approximately N = 1,166 participants, and by 8) Mou et al (2020) with k = 40 studies on “robot personality”. We additionally analyzed a recent meta-analysis not yet on Scopus, but in press.…”

Section: Confidence In Hri Researchmentioning

confidence: 99%

“…This heterogeneity of effects can also be a hint that HRI research is strongly context-sensitive (as has been predicted due to its similarities to social psychology) which likely means that HRI user studies are hard to replicate, effects are not as stable as hoped or that results can hardly be generalized across contexts. Furthermore, user studies in HRI seem to rely on very specific study participants such as samples from WEIRD (Western, Educated, Industrialized, Rich, Democratic) populations ( Esterwood et al, 2021 ; Stower et al, 2021 ) or student samples ( Baxter et al, 2016 ; Mara et al, 2021 ) and might not replicate in other populations.…”

Section: Confidence In Hri Researchmentioning

confidence: 99%

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Crisis Ahead? Why Human-Robot Interaction User Studies May Have Replicability Problems and Directions for Improvement

2022

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There is a confidence crisis in many scientific disciplines, in particular disciplines researching human behavior, as many effects of original experiments have not been replicated successfully in large-scale replication studies. While human-robot interaction (HRI) is an interdisciplinary research field, the study of human behavior, cognition and emotion in HRI plays also a vital part. Are HRI user studies facing the same problems as other fields and if so, what can be done to overcome them? In this article, we first give a short overview of the replicability crisis in behavioral sciences and its causes. In a second step, we estimate the replicability of HRI user studies mainly 1) by structural comparison of HRI research processes and practices with those of other disciplines with replicability issues, 2) by systematically reviewing meta-analyses of HRI user studies to identify parameters that are known to affect replicability, and 3) by summarizing first replication studies in HRI as direct evidence. Our findings suggest that HRI user studies often exhibit the same problems that caused the replicability crisis in many behavioral sciences, such as small sample sizes, lack of theory, or missing information in reported data. In order to improve the stability of future HRI research, we propose some statistical, methodological and social reforms. This article aims to provide a basis for further discussion and a potential outline for improvements in the field.

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Section: Meta-analyses In Hri Show Many Issuesmentioning

confidence: 53%

Section: Confidence In Hri Researchmentioning

confidence: 71%

Section: Confidence In Hri Researchmentioning

confidence: 99%

Section: Confidence In Hri Researchmentioning

confidence: 99%

See 2 more Smart Citations

Crisis Ahead? Why Human-Robot Interaction User Studies May Have Replicability Problems and Directions for Improvement

2022

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“…Humans and robots are increasingly finding themselves in collaborative work arrangements [8], [9], [10], [11], [12]. Trust is vital to promoting human and robot collaboration, but like human teammates robots make mistakes that undermine trust.…”

Section: Introductionmentioning

confidence: 99%

Do You Still Trust Me? Human-Robot Trust Repair Strategies

Esterwood

Robert

2021

2021 30th IEEE International Conference on Robot &Amp; Human Interactive Communication (RO-MAN)

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Trust is vital to promoting human and robot collaboration, but like human teammates, robots make mistakes that undermine trust. As a result, a human's perception of his or her robot teammate's trustworthiness can dramatically decrease [1], [2], [3], [4]. Trustworthiness consists of three distinct dimensions: ability (i.e. competency), benevolence (i.e. concern for the trustor) and integrity (i.e. honesty) [5], [6]. Taken together, decreases in trustworthiness decreases trust in the robot [7]. To address this, we conducted a 2 (high vs. low anthropomorphism) x 4 (trust repair strategies) between-subjects experiment. Preliminary results of the first 164 participants (between 19 and 24 per cell) highlight which repair strategies are effective relative to ability, integrity and benevolence and the robot's anthropomorphism. Overall, this paper contributes to the HRI trust repair literature.

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Lonely human and dominant robot: Similarity versus complementary attraction

Yu,

Fan

2024

Psychology and Marketing

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While social robots can provide companionship, people hesitate to connect with them. This research delves into a neglected question: How can we enhance the probability of potential users, especially those grappling with loneliness, connecting with companion robots to fulfill their social needs? Building upon the friendliness–dominance model and attraction theory in social psychology, our six studies reveal that individuals experiencing greater loneliness hold generally less favorable attitudes toward the idea of adopting robotic companionship. However, lonelier individuals show a higher inclination to bond with robots that act submissive rather than dominant ones. This research contributes to the understanding of human–robot interaction by examining how human traits and their perceptions of robot personalities jointly influence the interaction. The results have significant implications for guiding the design of robot product attributes to enhance their appeal to individuals experiencing varying degrees of loneliness.

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A Meta-Analysis of Human Personality and Robot Acceptance in Human-Robot Interaction

Cited by 12 publications

References 61 publications

Crisis Ahead? Why Human-Robot Interaction User Studies May Have Replicability Problems and Directions for Improvement

Crisis Ahead? Why Human-Robot Interaction User Studies May Have Replicability Problems and Directions for Improvement

Do You Still Trust Me? Human-Robot Trust Repair Strategies

Lonely human and dominant robot: Similarity versus complementary attraction

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