Rethinking Trust Repair in Human-Robot Interaction

As robots become increasingly prevalent in work-oriented collaborations, trust has emerged as a critical factor in their acceptance and effectiveness. However, trust is dynamic and can erode when mistakes are made. Despite emerging research on trust repair in human-robot interaction, significant questions remain about identifying reliable approaches to restoring trust in robots after trust violations occur. To address this problem, my research aims to identify effective strategies for designing robots capable of trust repair in human-robot interaction (HRI) and to explore the underlying mechanisms that make these strategies successful. This paper provides an overview of the fundamental concepts and key components of the trust repair process in HRI, as well as a summary of my current published work in this area. Additionally, I discuss the research questions that will guide my future work and the potential contributions that this research could make to the field.Comment: Pre-Print of Submission for CSCW 2023 Doctoral Consortiu

Personality in Healthcare Human Robot Interaction (H-HRI): A Literature Review and Brief Critique

Robots are becoming an important way to deliver health care, and personality is vital to understanding their effectiveness. Despite this, there is a lack of a systematic overarching understanding of personality in health care human robot interaction (H-HRI). To address this, the authors conducted a review that identified 18 studies on personality in H-HRI. This paper presents the results of that systematic literature review. Insights are derived from this review regarding the methodologies, outcomes, and samples utilized. The authors of this review discuss findings across this literature while identifying several gaps worthy of attention. Overall, this paper is an important starting point in understanding personality in H-HRI.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156252/1/Esterwood and Robert 2020.pdfDescription of Esterwood and Robert 2020.pdf : ArticleSEL

Robots and COVID-19: Re-imagining Human–Robot Collaborative Work in Terms of Reducing Risks to Essential Workers

The COVID-19 pandemic has led to the widespread adoption of physical distancing to prevent the disease’s spread. Physical distancing, however, is not always feasible for essential workers. Robots are one proposed solution to help ensure that essential work is performed while reducing the risk of COVID-19 exposure among essential workers and their families. The COVID-19 pandemic has, however, highlighted the ability and inability of robots to directly replace human labor. At present, much of the discussion has focused on the need for technical developments in robotics. This perspective is short-sighted because it and fails to leverage the collaborative nature of work between humans and robots. In response, this article acts as a call to shift the conversation away from technical developments and toward a focus on human and robot work redesign.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/165332/1/Robonomics Editorial Jan 16 2021 (Posted).pdfDescription of Robonomics Editorial Jan 16 2021 (Posted).pdf : PreprintSEL

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

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. Trustworthiness consists of three distinct dimensions: ability (i.e. competency), benevolence (i.e. concern for the trustor) and integrity (i.e. honesty). Taken together, decreases in trustworthiness decreases trust in the robot. 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.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/168396/1/Esterwood and Robert 2021.pdfDescription of Esterwood and Robert 2021.pdf : PreprintSEL

Having The Right Attitude: How Attitude Impacts Trust Repair in Human-Robot Interaction,

Robot co-workers, like human co-workers, make mistakes that undermine trust. Yet, trust is just as important in promoting human–robot collaboration as it is in promoting human–human collaboration. In addition, individuals can significantly differ in their attitudes toward robots, which can also impact or hinder their trust in robots. To better understand how individual attitude can influence trust repair strategies, we propose a theoretical model that draws from the theory of cognitive dissonance. To empirically verify this model, we conducted a between-subjects experiment with 100 participants assigned to one of four repair strategies (apologies, denials, explanations, or promises) over three trust violations. Individual attitudes did moderate the efficacy of repair strategies and this effect differed over successive trust violations. Specifically, repair strategies were most effective relative to individual attitude during the second of the three trust violations, and promises were the trust repair strategy most impacted by an individual’s attitude.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/171268/1/Esterwood and Roboert 2022 HRI.pdfDescription of Esterwood and Roboert 2022 HRI.pdf : PreprintSEL

A Systematic Review of Human and Robot Personality in Healthcare Human-Robot Interaction

Robots have become vital to the delivery of healthcare and their personalities are often important to understanding their effectiveness as health care providers. Despite this, there is a lack of a systematic overarching understanding of personality in health care human-robot interaction. This makes it difficult to understand what we know and do not know about the impact of personality in health care human-robot interaction (H-HRI). As a result, our understanding of personality in H-HRI has not kept pace with the deployment of robots in various health care environments. To address this, the authors conducted a literature review that identified 18 studies on personality in H-HRI. This paper expands, refines, and further explicates the systematic review done in a conference proceedings [see: Esterwood (Proceedings of the 8th International Conference on Human-Agent Interaction, 2020, 87–95)]. Review results: 1) highlight major thematic research areas, 2) derive and present major conclusions from the literature, 3) identify gaps in the literature, and 4) offer guidance for future H-HRI researchers. Overall, this paper represents a reflection on the existing literature and provides an important starting point for future research on personality in H-HRI.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/169549/1/Esterwood and Robert 2021 FRAI (Published).pdfDescription of Esterwood and Robert 2021 FRAI (Published).pdf : ArticleSEL

Barriers to AV Bus Acceptance: A U.S. National Survey and Research Agenda

Automated Vehicle (AV) buses hold great potential, yet it is not clear if Americans will choose to ride them. Trust and attitudes, often influenced by individual differences, are vital predictors of technology acceptance and AVs are no exception. To deepen our understanding of individual differences as they pertain to AV buses, this paper presents the results of a national survey of 401 participants located in the United States of America. Findings from this survey indicate that individual differences influenced trust, attitude, and intention to ride AV buses. Specifically, trust in AV buses differed by individual's age and bus riding frequency while attitudes toward AV buses differed by individual's age, ethnicity, and bus riding frequency. Finally, intention to ride an AV bus differed by age, gender, ethnicity, and bus riding frequency. Based on these results, we propose a research agenda that seeks to inform future research on acceptance of AV buses.M-City research o ce under the University of Michigan O ce of ResearchPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166098/1/Esterwood et al. 2021.pdfDescription of Esterwood et al. 2021.pdf : PreprintSEL

A Review of Personality in Human Robot Interactions

Personality has been identified as a vital factor in understanding the quality of human robot interactions. Despite this the research in this area remains fragmented and lacks a coherent framework. This makes it difficult to understand what we know and identify what we do not. As a result our knowledge of personality in human robot interactions has not kept pace with the deployment of robots in organizations or in our broader society. To address this shortcoming, this paper reviews 83 articles and 84 separate studies to assess the current state of human robot personality research. This review: (1) highlights major thematic research areas, (2) identifies gaps in the literature, (3) derives and presents major conclusions from the literature and (4) offers guidance for future research.Comment: 70 pages, 2 figure

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

Human personality has been identified as a predictor of robot acceptance in the human robot interaction (HRI) literature. Despite this, the HRI literature has provided mixed support for this assertion. To better understand the relationship between human personality and robot acceptance, this paper conducts a meta-analysis of 26 studies. Results found a positive relationship between human personality and robot acceptance. However, this relationship varied greatly by the specific personality trait along with the study sample’s age, gender diversity, task, and global region. This meta-analysis also identified gaps in the literature. Namely, additional studies are needed that investigate both the big five personality traits and other personality traits, examine a more diverse age range, and utilize samples from previously unexamined regions of the globe.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/165339/1/Esterwood et al. 2021 (one column).pdfDescription of Esterwood et al. 2021 (one column).pdf : Preprint one column versionSEL