research-article

The Trusted Listener: The Influence of Anthropomorphic Eye Design of Social Robots on User's Perception of Trustworthiness

Authors:

Danni ChangAuthors Info & Claims

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Article No.: 571, Pages 1 - 13

https://doi.org/10.1145/3491102.3517670

Published: 29 April 2022 Publication History

Abstract

Nowadays, social robots have become human's important companions. The anthropomorphic features of robots, which are important in building natural user experience and trustable human-robot partnership, have attracted increasing attention. Among these features, eyes attract most audience's attention and are particularly important. This study aims to investigate the influence of robot eye design on users’ trustworthiness perception. Specifically, a simulation robot model was developed. Three sets of experiments involving sixty-six participants were conducted to investigate the effects of (i) visual complexity of eye design, (ii) blink rate, and (iii) gaze aversion of social robots on users’ perceived trustworthiness. Results indicate that high visual complexity and gaze aversion lead to higher perceived trustworthiness and reveal a positive correlation between the perceived anthropomorphic effect of eye design and users’ perceived trust, while a non-significant effect of blink rate has been found. Preliminary suggestions are provided for the design of social robots in future works.

References

[1]

Mohammad Soltani Delgosha and Nastaran Hajiheydari. 2021. How human users engage with consumer robots? A dual model of psychological ownership and trust to explain post-adoption behaviours. Computers in Human Behavior 117, 106660. DOI= http://dx.doi.org/10.1016/j.chb.2020.106660.

[2]

Aimi S. Ghazali, Jaap Ham, Emilia I. Barakova and Panos Markopoulos. 2018. Effects of Robot Facial Characteristics and Gender in Persuasive Human-Robot Interaction. Frontiers in Robotics and AI 5, 73 (2018-June-21). DOI= http://dx.doi.org/10.3389/frobt.2018.00073.

[3]

Matthew Marge, Carol Espy-Wilson, Nigel G Ward, Abeer Alwan, Yoav Artzi, Mohit Bansal, Gil Blankenship, Joyce Chai, Hal Daumé III and Debadeepta Dey. 2021. Spoken language interaction with robots: Recommendations for future research. Computer Speech & Language, 101255.

[4]

Lu Lu, Pei Zhang and Tingting Zhang. 2021. Leveraging “human-likeness” of robotic service at restaurants. International Journal of Hospitality Management 94, 102823. DOI= http://dx.doi.org/10.1016/j.ijhm.2020.102823.

[5]

Tian Xu, Hui Zhang and Chen Yu. 2016. See You See Me. ACM Transactions on Interactive Intelligent Systems 6, 1, 1-22. DOI= http://dx.doi.org/10.1145/2882970.

Digital Library

[6]

Anna Zinina, Liudmila Zaidelman, Nikita Arinkin and Artemiy Kotov. 2020. Non-verbal behavior of the robot companion: a contribution to the likeability. Procedia Computer Science 169, 800-806.

[7]

Ichiroh Kanaya, Shoichi Doi, Shohei Nakamura and Kazuo Kawasaki. Facial design for humanoid robot ACM Press. DOI= http://dx.doi.org/10.1145/2350046.2350077.

Digital Library

[8]

Chris Chesher and Fiona Andreallo. 2021. Eye Machines: Robot Eye, Vision and Gaze. International journal of social robotics. DOI= http://dx.doi.org/10.1007/s12369-021-00777-7.

[9]

Yuki Okafuji, Jun Baba, Junya Nakanishi, Itaru Kuramoto, Kohei Ogawa, Yuichiro Yoshikawa and Hiroshi Ishiguro. 2020. Can a humanoid robot continue to draw attention in an office environment? Advanced Robotics 34, 14, 931-946. DOI= http://dx.doi.org/10.1080/01691864.2020.1769724.

[10]

Henny Admoni and Brian Scassellati. 2017. Social Eye Gaze in Human-Robot Interaction: A Review. Journal of Human-Robot Interaction 6, 1, 25. DOI= http://dx.doi.org/10.5898/jhri.6.1.admoni.

Digital Library

[11]

Sean Andrist, Bilge Mutlu and Adriana Tapus. 2015. Look Like Me: Matching Robot Personality via Gaze to Increase Motivation. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems.

Digital Library

[12]

Michal Luria, Jodi Forlizzi and Jessica Hodgins. 2018. The effects of eye design on the perception of social robots. In 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) IEEE, 1032-1037.

Digital Library

[13]

Yao Song and Yan Luximon. 2021. The face of trust: The effect of robot face ratio on consumer preference. Computers in Human Behavior 116, 106620. DOI= http://dx.doi.org/10.1016/j.chb.2020.106620.

[14]

Yao Song, Ameersing Luximon and Yan Luximon. 2021. The effect of facial features on facial anthropomorphic trustworthiness in social robots. Applied Ergonomics 94, 103420.

[15]

Elizabeth Phillips, Xuan Zhao, Daniel Ullman and Bertram F. Malle. What is Human-like? ACM. DOI= http://dx.doi.org/10.1145/3171221.3171268.

Digital Library

[16]

Alisa Kalegina, Grace Schroeder, Aidan Allchin, Keara Berlin and Maya Cakmak. 2018. Characterizing the design space of rendered robot faces. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, 96-104.

Digital Library

[17]

Simon Coghlan. 2021. Robots and the Possibility of Humanistic Care. International journal of social robotics, 1-14.

[18]

Luis-Alberto Perez-Gaspar, Santiago-Omar Caballero-Morales and Felipe Trujillo-Romero. 2016. Multimodal emotion recognition with evolutionary computation for human-robot interaction. Expert Systems with Applications 66, 42-61.

Digital Library

[19]

Terrence Fong, Illah Nourbakhsh and Kerstin Dautenhahn. 2003. A survey of socially interactive robots. Robotics and Autonomous Systems 42, 3-4, 143-166. DOI= http://dx.doi.org/10.1016/s0921-8890(02)00372-x.

[20]

Fei Yan, Abdullah M. Iliyasu and Kaoru Hirota. 2021. Emotion space modelling for social robots. Engineering Applications of Artificial Intelligence 100, 104178. DOI= http://dx.doi.org/10.1016/j.engappai.2021.104178.

[21]

Giuliana Ferrante, Gianpaolo Vitale, Amelia Licari, Laura Montalbano, Giovanni Pilato, Ignazio Infantino, Agnese Augello and Stefania La Grutta. 2020. Social robots and therapeutic adherence: A new challenge in pediatric asthma? Paediatric Respiratory Reviews. DOI= http://dx.doi.org/10.1016/j.prrv.2020.11.001.

[22]

Huili Chen, Hae Won Park and Cynthia Breazeal. 2020. Teaching and learning with children: Impact of reciprocal peer learning with a social robot on children's learning and emotive engagement. Computers & Education 150, 103836.

Digital Library

[23]

Wonjoon Kim, Nayoung Kim, Joseph B Lyons and Chang S Nam. 2020. Factors affecting trust in high-vulnerability human-robot interaction contexts: A structural equation modelling approach. Applied Ergonomics 85, 103056.

[24]

Terhi M. Helminen, Suvi M. Kaasinen and Jari K. Hietanen. 2011. Eye contact and arousal: The effects of stimulus duration. Biological Psychology 88, 1, 124-130. DOI= http://dx.doi.org/10.1016/j.biopsycho.2011.07.002.

[25]

Jari K Hietanen. 2018. Affective eye contact: an integrative review. Frontiers in psychology 9, 1587.

[26]

Chien-Ming Huang and Bilge Mutlu. 2013. Modeling and Evaluating Narrative Gestures for Humanlike Robots. In Robotics: Science and Systems, 57-64.

[27]

Bilge Mutlu, Toshiyuki Shiwa, Takayuki Kanda, Hiroshi Ishiguro and Norihiro Hagita. Footing in human-robot conversations ACM Press. DOI= http://dx.doi.org/10.1145/1514095.1514109.

Digital Library

[28]

Spatola Nicolas and Wykowska Agnieszka. 2021. The personality of anthropomorphism: How the need for cognition and the need for closure define attitudes and anthropomorphic attributions toward robots. Computers in Human Behavior 122, 106841.

[29]

Brian R Duffy. 2003. Anthropomorphism and the social robot. Robotics and Autonomous Systems 42, 3-4, 177-190.

[30]

Lara Christoforakos, Alessio Gallucci, Tinatini Surmava-Große, Daniel Ullrich and Sarah Diefenbach. 2021. Can Robots Earn Our Trust the Same Way Humans Do? A Systematic Exploration of Competence, Warmth, and Anthropomorphism as Determinants of Trust Development in HRI. Frontiers in Robotics and AI 8, 79 (2021-April-09). DOI= http://dx.doi.org/10.3389/frobt.2021.640444.

[31]

Helena Kiilavuori, Veikko Sariola, Mikko J. Peltola and Jari K. Hietanen. 2021. Making eye contact with a robot: Psychophysiological responses to eye contact with a human and with a humanoid robot. Biological Psychology 158, 107989. DOI= http://dx.doi.org/10.1016/j.biopsycho.2020.107989.

[32]

Tomomi Onuki, Takafumi Ishinoda, Yoshinori Kobayashi and Yoshinori Kuno. 2013. Design of robot eyes suitable for gaze communication. In 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI) IEEE, 203-204.

[33]

Carl F DiSalvo, Francine Gemperle, Jodi Forlizzi and Sara Kiesler. 2002. All robots are not created equal: the design and perception of humanoid robot heads. In Proceedings of the 4th conference on Designing interactive systems: processes, practices, methods, and techniques, 321-326.

Digital Library

[34]

K. Ruhland, C. E. Peters, S. Andrist, J. B. Badler, N. I. Badler, M. Gleicher, B. Mutlu and R. McDonnell. 2015. A Review of Eye Gaze in Virtual Agents, Social Robotics and HCI: Behaviour Generation, User Interaction and Perception. Computer Graphics Forum 34, 6, 299-326. DOI= http://dx.doi.org/10.1111/cgf.12603.

Digital Library

[35]

Kaname Sano, Keisuke Murata, Ryota Suzuki, Yoshinori Kuno, Daijiro Itagaki and Yoshinori Kobayashi. Museum Guide Robot by Considering Static and Dynamic Gaze Expressions to Communicate with Visitors ACM. DOI= http://dx.doi.org/10.1145/2701973.2702011.

Digital Library

[36]

Sean Andrist, Xiang Zhi Tan, Michael Gleicher and Bilge Mutlu. 2014. Conversational gaze aversion for humanlike robots. In 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI) IEEE, 25-32.

Digital Library

[37]

Laura C. Trutoiu, Elizabeth J. Carter, Iain Matthews and Jessica K. Hodgins. 2011. Modeling and animating eye blinks. ACM Transactions on Applied Perception 8, 3, 1-17. DOI= http://dx.doi.org/10.1145/2010325.2010327.

Digital Library

[38]

Siyuan Chen, Julien Epps, Natalie Ruiz and Fang Chen. Eye activity as a measure of human mental effort in HCI ACM Press. DOI= http://dx.doi.org/10.1145/1943403.1943454.

Digital Library

[39]

Antonio Maffei and Alessandro Angrilli. 2019. Spontaneous blink rate as an index of attention and emotion during film clips viewing. Physiology & Behavior 204, 256-263. DOI= http://dx.doi.org/10.1016/j.physbeh.2019.02.037.

[40]

Hang Li, Julien Epps and Siyuan Chen. 2020. Think before you speak: An investigation of eye activity patterns during conversations using eyewear. International Journal of Human-Computer Studies 143, 102468.

[41]

S Venus Jin and Seounmi Youn. 2021. Why do consumers with social phobia prefer anthropomorphic customer service chatbots? Evolutionary explanations of the moderating roles of social phobia. Telematics and Informatics 62, 101644.

[42]

Christoph Bartneck, Takayuki Kanda, Omar Mubin and Abdullah Al Mahmud. 2009. Does the design of a robot influence its animacy and perceived intelligence? International journal of social robotics 1, 2, 195-204.

[43]

Corina Pelau, Dan-Cristian Dabija and Irina Ene. 2021. What makes an AI device human-like? The role of interaction quality, empathy and perceived psychological anthropomorphic characteristics in the acceptance of artificial intelligence in the service industry. Computers in Human Behavior 122, 106855.

[44]

Maike Paetzel-Prüsmann, Giulia Perugia and Ginevra Castellano. 2021. The Influence of robot personality on the development of uncanny feelings. Computers in Human Behavior 120, 106756. DOI= http://dx.doi.org/10.1016/j.chb.2021.106756.

Digital Library

[45]

Markus Appel, Birgit Lugrin, Mayla Kühle and Corinna Heindl. 2021. The emotional robotic storyteller: On the influence of affect congruency on narrative transportation, robot perception, and persuasion. Computers in Human Behavior 120, 106749.

Digital Library

[46]

Jakub Złotowski, Diane Proudfoot, Kumar Yogeeswaran and Christoph Bartneck. 2015. Anthropomorphism: opportunities and challenges in human–robot interaction. International journal of social robotics 7, 3, 347-360.

Cited By

Campagna GRehm M(2024)A Systematic Review of Trust Assessments in Human–Robot InteractionACM Transactions on Human-Robot Interaction10.1145/370612314:2(1-35)Online publication date: 29-Nov-2024
https://dl.acm.org/doi/10.1145/3706123
Matheus KVázquez MScassellati B(2024)Ommie: The Design and Development of a Social Robot for Anxiety ReductionACM Transactions on Human-Robot Interaction10.1145/370612214:2(1-34)Online publication date: 5-Dec-2024
https://dl.acm.org/doi/10.1145/3706122
Candello HSoella GNascimento L(2024)Designing multi-model conversational AI financial systems: understanding sensitive values of women entrepreneurs in BrazilProceedings of the 2024 ACM International Conference on Interactive Media Experiences Workshops10.1145/3672406.3672409(11-18)Online publication date: 12-Jun-2024
https://dl.acm.org/doi/10.1145/3672406.3672409
Show More Cited By

Index Terms

The Trusted Listener: The Influence of Anthropomorphic Eye Design of Social Robots on User's Perception of Trustworthiness
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI

Recommendations

Understanding Privacy-friendly Design of Robot Eyes
HAI '23: Proceedings of the 11th International Conference on Human-Agent Interaction

Eyes have been widely found to play an important role in communicating emotions and intentions for social robots. However, when introducing robots with eyes into people’s personal living spaces, it is necessary to consider how the social aspects of a ...
Follow Me: Anthropomorphic Appearance and Communication Impact Social Perception and Joint Navigation Behavior
HRI '24: Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction

This study addresses how anthropomorphic features shape users' social perception and trust towards service robots and whether anthropomorphic characteristics influence the way people jointly navigate with them facing several obstacles in a course. ...
Study on Acceptance of Social Robots by Aging Adults Living Alone
HCI International 2020 – Late Breaking Papers: Universal Access and Inclusive Design
Abstract
Social robots have become an important way to alleviate the impact of aging on society and families. This study aims to explore the influence of the living state of the elderly on robot acceptance. Based on Unified Theory of Acceptance and Use of ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

April 2022

10459 pages

ISBN:9781450391573

DOI:10.1145/3491102

Editors:
Simone Barbosa
PUC-Rio, Brazil
,
Cliff Lampe
University of Michigan, USA
,
Caroline Appert
Université Paris-Saclay, France
,
David A. Shamma
Toyota Research Institute, USA
,
Steven Drucker
Microsoft Research, USA
,
Julie Williamson
University of Glasgow, UK
,
Koji Yatani
University of Tokyo, Japan

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 April 2022

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

CHI '22

Sponsor:

SIGCHI

CHI '22: CHI Conference on Human Factors in Computing Systems

April 29 - May 5, 2022

LA, New Orleans, USA

Acceptance Rates

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

Upcoming Conference

CHI 2025

Sponsor:
sigchi

ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
1,138
Total Downloads

Downloads (Last 12 months)273
Downloads (Last 6 weeks)29

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Campagna GRehm M(2024)A Systematic Review of Trust Assessments in Human–Robot InteractionACM Transactions on Human-Robot Interaction10.1145/370612314:2(1-35)Online publication date: 29-Nov-2024
https://dl.acm.org/doi/10.1145/3706123
Matheus KVázquez MScassellati B(2024)Ommie: The Design and Development of a Social Robot for Anxiety ReductionACM Transactions on Human-Robot Interaction10.1145/370612214:2(1-34)Online publication date: 5-Dec-2024
https://dl.acm.org/doi/10.1145/3706122
Candello HSoella GNascimento L(2024)Designing multi-model conversational AI financial systems: understanding sensitive values of women entrepreneurs in BrazilProceedings of the 2024 ACM International Conference on Interactive Media Experiences Workshops10.1145/3672406.3672409(11-18)Online publication date: 12-Jun-2024
https://dl.acm.org/doi/10.1145/3672406.3672409
Ashwini BGhoshal ASuri VAchary KShukla J(2024)“It looks useful, works just fine, but will it replace me ?" Understanding Special Educators’ Perception of Social Robots for Autism Care in IndiaProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642836(1-23)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642836
Maroto‐Gómez MFernández‐Rodicio ECastro‐González ÁMalfaz MSalichs M(2024)Evaluating Users’ Perception of Biologically Inspired Involuntary Behavior in Human–Robot InteractionAdvanced Intelligent Systems10.1002/aisy.2024000426:10Online publication date: 29-Sep-2024
https://doi.org/10.1002/aisy.202400042
Herath ASallam SSakamoto YGomez RIrani P(2023)Exploring the Design of Social Robot User Interfaces for Presenting Data-Driven StoriesProceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia10.1145/3626705.3627781(321-339)Online publication date: 3-Dec-2023
https://dl.acm.org/doi/10.1145/3626705.3627781
Sakamoto YHerath AVuradi TSallam SGomez RIrani P(2023)How Should a Social Robot Deliver Negative Feedback Without Creating Distance Between the Robot and Child Users?Proceedings of the 11th International Conference on Human-Agent Interaction10.1145/3623809.3623882(325-334)Online publication date: 4-Dec-2023
https://dl.acm.org/doi/10.1145/3623809.3623882
Wang YWijenayake SHoggenmüller MHespanhol LWorrall STomitsch M(2023)My Eyes Speak: Improving Perceived Sociability of Autonomous Vehicles in Shared Spaces Through Emotional Robotic EyesProceedings of the ACM on Human-Computer Interaction10.1145/36042617:MHCI(1-30)Online publication date: 13-Sep-2023
https://dl.acm.org/doi/10.1145/3604261
Candello HSoella GSanctos CGrave MDe Brito Filho A(2023)"This means nothing to me": Building credibility in conversational systemsProceedings of the 5th International Conference on Conversational User Interfaces10.1145/3571884.3603759(1-6)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3571884.3603759

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Figures

Tables

Media

View Table of Conten