The application of anthropomorphic features to robots is generally considered to be beneficial for human- robot interaction. Although previous research has mainly focused on social robots, the phenomenon gains increasing attention in industrial human-robot interaction, as well. In this study, the impact of anthropomorphic design of a collaborative industrial robot on the dynamics of trust is examined. Participants interacted with a robot, which was either anthropomorphically or technically designed and experienced either a comprehensible or an incomprehensible fault of the robot. Unexpectedly, the robot was perceived as less reliable in the anthropomorphic condition. Additionally, trust increased after faultless experience and decreased after failure experience independently of the type of error. Even though the manipulation of the design did not result in a different perception of the robot’s anthropomorphism, it still influenced the formation of trust. The results emphasize that anthropomorphism is no universal remedy to increase trust, but highly context dependent.
Get full access to this article
View all access options for this article.
References
1.
BartneckC.KulićD.CroftE.ZoghbiS. (2009). Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. International Journal of Social Robotics, 1(1), 71–81. https://doi.org/10.1007/s12369-008-0001-3
2.
CharalambousG.FletcherS.WebbP. (2016). The development of a scale to evaluate trust in industrial human-robot collaboration. International Journal of Social Robotics, 8(2), 193–209. https://doi.org/10.1007/s12369-015-0333-8
FeuerbergB.V.BahnerJ.E.ManzeyD. (2005). Interindividuelle Unterschiede im Umgang mit Automation - Entwicklung eines Fragebogens zur Erfassung des Complacency. In UrbasL.SteffensC. (Eds.), Zustandserkennung und Systemgestaltung. 6. Berliner Werkstatt Mensch-Maschine-Systeme (pp. 199-202). VDI-Verlag.
5.
FrankeT.AttigC.WesselD. (2019). A personal resource for technology interaction: development and validation of the affinity for technology interaction (ATI) scale. International Journal of Human– Computer Interaction, 35(6), 456-467. https://doi.org/10.1080/10447318.2018.1456150
6.
HancockP. A.BillingsD. R.SchaeferK. E.ChenJ. Y. C.De VisserE. J.ParasuramanR. (2011). A meta-analysis of factors affecting trust in human-robot interaction. Human Factors, 53(5), 517-527. https://doi.org/10.1177/0018720811417254
7.
HaringK. S.WatanabeK.MougenotC. (2013). The influence of robot appearance on assessment. In 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (pp. 131–132). IEEE. https://doi.org/10.1109/HRI.2013.6483536
8.
HoC. C.MacDormanK. F. (2010). Revisiting the uncanny valley theory: Developing and validating an alternative to the Godspeed indices. Computers in Human Behavior, 26(6), 1508–1518. https://doi.org/10.1016/J.CHB.2010.05.015
9.
KieslerS.PowersA.FussellS. R.TorreyC. (2008). Anthropomorphic interactions with a robot and robot-like agent. Social Cognition, 26(2), 169–181. https://doi.org/10.1521/soco.2008.26.2.169
10.
KuzS.MayerM. P.MüllerS.SchlickC. M. (2013). Using anthropomorphism to improve the human-machine interaction in industrial environments (Part I). In International Conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management (pp. 76-85). Springer. https://doi.org/10.1007/978-3-642-39182-8_9
LewisM.SycaraK.WalkerP. (2018). The role of trust in human-robot interaction. In Foundations of trusted autonomy (pp. 135-159). Springer. https://doi.org/10.1007/978-3-319-64816-3_8
13.
MadhavanP.WiegmannD. A.LacsonF. C. (2006). Automation failures on tasks easily performed by operators undermine trust in automated aids. Human Factors, 48(2), 241–256. https://doi.org/10.1518/001872006777724408
14.
OnnaschL.RoeslerE.(2019). Anthropomorphizing Robots: The Effect of Framing in Human-Robot Collaboration. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 63(1), 1311–1315. https://doi.org/10.1177/1071181319631209
15.
OnnaschL.RoeslerE. (in press). A taxonomy to structure and analyze human-robot interaction. International Journal of Social Robotics.
16.
SalemM.LakatosG.AmirabdollahianF.DautenhahnK. (2015). Would you trust a (faulty) robot? Effects of error, task type and personality on human-robot cooperation and trust. In 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (pp. 1-8). IEEE. https://doi.org/10.1145/2696454.2696497
17.
SarkarS.Araiza-IllanD.EderK. (2017). Effects of faults, experience, and personality on trust in a robot co-worker. arXiv preprint arXiv:1703.02335.
18.
SyrdalD. S.DautenhahnK.KoayK. L.WaltersM. L. (2009). The negative attitudes towards robots scale and reactions to robot behaviour in a live human-robot interaction study. Adaptive and Emergent Behaviour and Complex Systems - Proceedings of the 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour, AISB 2009, (pp. 109–115). SSAISB.
19.
WaytzA.CacioppoJ.EpleyN. (2010). Who sees human? The stability and importance of individual differences in anthropomorphism. Perspectives on Psychological Science, 5(3), 219–232. https://doi.org/10.1177/1745691610369336
