Skip to main content
Log in

Do Robot Performance and Behavioral Style affect Human Trust?

A Multi-Method Approach

  • Published:
International Journal of Social Robotics Aims and scope Submit manuscript

Abstract

An important aspect of a robot’s social behavior is to convey the right amount of trustworthiness. Task performance has shown to be an important source for trustworthiness judgments. Here, we argue that factors such as a robot’s behavioral style can play an important role as well. Our approach to studying the effects of a robot’s performance and behavioral style on human trust involves experiments with simulated robots in video human–robot interaction (VHRI) and immersive virtual environments (IVE). Although VHRI and IVE settings cannot substitute for the genuine interaction with a real robot, they can provide useful complementary approaches to experimental research in social human robot interaction. VHRI enables rapid prototyping of robot behaviors. Simulating human–robot interaction in IVEs can be a useful tool for measuring human responses to robots and help avoid the many constraints caused by real-world hardware. However, there are also difficulties with the generalization of results from one setting (e.g., VHRI) to another (e.g. IVE or the real world), which we discuss. In this paper, we use animated robot avatars in VHRI to rapidly identify robot behavioral styles that affect human trust assessment of the robot. In a subsequent study, we use an IVE to measure behavioral interaction between humans and an animated robot avatar equipped with behaviors from the VHRI experiment. Our findings reconfirm that a robot’s task performance influences its trustworthiness, but the effect of the behavioral style identified in the VHRI study did not influence the robot’s trustworthiness in the IVE study.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Notes

  1. In the trust game [18], participants must decide whether to invest money in a partner in an uncertain context. The partner receives this money, multiplied by a factor (usually 3 or 4). The partner must then decide whether to reciprocate the trust by sending back some of the money, resulting in a net gain for both players, or keeping all the money for themselves.

  2. The gender ratio of the participant pools of both experiments is skewed towards female. Although this has no consequence when comparing the results from the two experiments in this work, it may limit the external validity of these studies.

  3. Autonomy (‘How much did you feel the robot acted on its own’) and Robot-like behavior (‘How much did you feel the robot acted like you would expect from a robot’) were also measured as exploratory questions. Their results can be found in the supplementary materials.

  4. A multivariate analysis of variance on all manipulation checks was also performed; apart from the expected main effects shown here, we also found some side effects. These can be found in the appendix.

  5. It is also possible to analyze Experiment 2 by means of the single item measure of trustworthiness, which yields results similar to the analysis of the compound measure reported below.

  6. As in Experiment 1, Autonomy and Robot-like behavior were also measured as exploratory questions at the end of the questionnaire. No significant effects were found for autonomy, all \(F\)s \(<1.1\), all \(p\)s \(> .05\). There was a significant main effect of task performance on robot-like behavior, \(F\)(1,77) = 12.01, \(p <\) .001, \(\eta _p^2 =\) .13, indicating that a well performing robot was judged more robot-like (\(M =\) 4.86, \(SD =\) 1.41) than a badly performing robot (\(M =\) 3.62, \(SD =\) 1.79). No other effects were significant, all \(F\)s \(< 1\), all \(p\)s \(> .05\).

References

  1. Young JE, Hawkins R, Sharlin E, Igarashi T (2009) Toward acceptable domestic obots: applying insights from social psychology. Int J Soc Robot 1:95–108

    Article  Google Scholar 

  2. Sztompka P (1999) Trust: a social theory. Cambridge University Press, Cambridge

    Google Scholar 

  3. Sanfey A (2007) Social decision-making: insights from game theory and neuroscience. Science 318:598–602

    Article  Google Scholar 

  4. Mayer R, Davis J, Schoorman F (1995) An integrative model of organizational trust. Acad Manag Rev 20(3):709–734

    Google Scholar 

  5. Schoorman F, Mayer R, Davis J (2007) An integrative model of organizational trust: past, present, and future. Acad Manag Rev 32(2):344–354

    Article  Google Scholar 

  6. Simpson JA (2007) Psychological foundations of trust. Curr Dir Psychol Sci 16(5):264–268

    Article  Google Scholar 

  7. Lee J, See K (2004) Trust in automation: designing for appropriate reliance. Hum Factors 46(1):50–80

    Article  Google Scholar 

  8. Axelrod R, Hamilton WD (1981) The evolution of cooperation. Science 211(4491):1390–1396

    Article  MATH  MathSciNet  Google Scholar 

  9. Willis J, Todorov A (2006) First impressions: making up your mind after a 100-Ms exposure to a face. Psychol Sci 17(7):592–598

    Google Scholar 

  10. Oosterhof NN, Todorov A (2008) The functional basis of face evaluation. Proc Natl Acad Sci 105(32):11087–11092

    Article  Google Scholar 

  11. Dotsch R, Todorov A (2012) Reverse correlating social face perception. Soc Psychol Pers Sci 3(5):562–571. doi:10.1177/1948550611430272

    Google Scholar 

  12. Kaul TJ, Schmidt LD (1971) Dimensions of interviewer trustworthiness. J Couns Psychol 18(6):542–548. doi:10.1037/h0031748

    Article  Google Scholar 

  13. Roll WV, D SL, Kaul TJ (1972) Perceived interviewer trustworthiness among black and white convicts. J Couns Psychol 19(6):537–541

    Article  Google Scholar 

  14. Hancock PA, Billings DR, Schaefer KE, Chen JYC, de Visser EJ, Parasuraman R (2011) A meta-analysis of factors affecting trust in human–robot interaction. Hum Factors 53(5):517–527

    Article  Google Scholar 

  15. DeSteno D, Breazeal C, Frank RH, Pizarro D, Baumann J, Dickens L, Lee JJ (2012) Detecting the trustworthiness of novel partners in economic exchange. Psychol Sci 20(10):1–8. doi:10.1177/0956797612448793

    Google Scholar 

  16. Petty RE, Cacioppo JT (1986) Communication and persuasion: central and peripheral routes to attitude change. Springer, New York

    Book  Google Scholar 

  17. Brewer MB (1988) A dual process model of impression formation. Erlbaum Associates, Hillsdale

    Google Scholar 

  18. Berg J, Dickhaut J, McCabe K (1995) Trust, reciprocity, and social history. Games Econ Behav 10(1):122–142

    Article  MATH  Google Scholar 

  19. van ’t Wout M (2008) Friend or foe: the effect of implicit trustworthiness judgments in social decision-making. Cognition 108:796–803

    Article  Google Scholar 

  20. Chang LJ, Doll BB, van ’t Wout M, Frank MJ (2010) Seeing is believing: trustworthiness as a dynamic belief. Cogn Psycho 61:87–105

    Article  Google Scholar 

  21. Mumm J, Mutlu B (2009) Human–robot proxemics: physical and psychological distancing in human–robot interaction. In: Proceedings of artificial intelligence and simulation of behavior convention (AISB 09), Lausanne, Switzerland

  22. Takayama L, Pantofaru C (2009) Influences on proxemic behaviors in human–robot interaction. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE, St Louis, Missouri, pp 5495–5502

  23. Heerink M, Kröse B, Evers V, Wielinga B (2010) Relating conversational expressiveness to social presence and acceptance of an assistive social robot. Virtual Real 14:77–84

    Article  Google Scholar 

  24. Walters ML, Lohse M, Hanheide M, Wrede B, Syrdal DS, Koay KL, Green A, Hüttenrauch H, Dautenhahn K, Sagerer G (2011) Evaluating the robot personality and verbal behavior of domestic robots using video-based studies. Adv Robot 25:2233–2254

    Article  Google Scholar 

  25. Walters ML (2008) The design space for robot appearance and behaviour for social robot companions. PhD Thesis, University of Hertfordshire

  26. Syrdal DS, Koay KL, Gácsi M, Walters ML, Dautenhahn K (2010) Video prototyping of dog-inspired non-verbal affective communication for an appearance constrained robot. In: Proceedings of the 19th IEEE international symposium on robot and human interative communication. Principe de Piemonte, Italy, pp 632–637

  27. Syrdal DS, Otero N, Dautenhahn K (2008) Video prototyping in human–robot interaction: results from a qualitative study. In: Abascal J, Fajardo I, Oakley I (eds) Proceedings of the 15th European congerence on cognitive ergonomics: the ergonomics of cool interaction. ACM New York, NY, Madeira, Portugal, pp 1–8

  28. Takayama L, Dooley D, Ju W (2011) Expressing thought: improving robot readability with animation principles. In: Proceedings of human–robot interaction conference: HRI 2011. Lausanne, Switzerland, pp 69–76

  29. Dautenhahn K (2007) Methodology & themes of human–robot interaction: a growing research field. Int J Adv Robot Syst 4(1):103–108

    Google Scholar 

  30. Blascovich J, Loomis J, Beall A, Swinth K, Hoyt C (2002) Immersive virtual environment technology as a research tool for social psychology. Psychol Inq 13(2):103–124

    Article  Google Scholar 

  31. Groom CJ, Sherman JW, Conrey FR (2002) What immersive virtual environments can offer to social cognition. Psychol Inq 13(2):125–128

    Article  Google Scholar 

  32. Dotsch R, Wigboldus DHJ (2008) Virtual prejudice. J Exp Soc Psychol 44:1194–1198

    Article  Google Scholar 

  33. Rinck M, Rörtgen T, Lange WG, Dotsch R, Wigboldus DHJ, Becker ES (2010) Social anxiety predicts avoidance behaviour in virtual encounters. Cogn & Emot 24(7):1269–1276. doi:10.1080/02699930903309268

    Article  Google Scholar 

  34. Rinck M, Kwakkenbos L, Dotsch R, Wigboldus DHJ, Becker ES (2010) Attentional and behavioural responses of spider fearfuls to virtual spiders. Cogn & Emot 24(7):1199–1206. doi:10.1080/02699930903135945

    Article  Google Scholar 

  35. Tikhanoff V, Cangelosi A, Metta G (2011) Integration of speech and action in humanoid robots: iCub simulation experiments. IEEE Trans Auton Ment Dev 3(1):17–29

    Article  Google Scholar 

  36. Woods S, Walters M, Koay KL, Dautenhahn K (2006) Comparing human robot interaction scenarios using live and video based methods: towards a novel methodological approach. In: Proceedings of the 9th IEEE international workshop on advanced motion control (AMC’06), New York. IEEE Press, Istanbul, Turkey, NY, pp 750–755

  37. Yagoda RE, Gillan DJ (2012) You want me to trust a ROBOT? The development of a human–robot interaction trust scale. Int J Soc Robot 4:235–248

    Article  Google Scholar 

  38. Bagheri N, Jamieson GA (2004) Considering subjective trust and montioring behavior in assessing automation-induced ”Complacency”. In: Proceedings of the human performance, situation awareness and automation conference, SA Technologies, Marietta, GA, pp 1–6

  39. Walters ML, Dautenhahn K, Te Boekhorst R, Koay KL, Syrdal DS, Nehaniv CL (2009) An empirical framework for human–robot proxemics. In: New frontiers in human–robot interaction, Edinburgh, Scotland

  40. Iwata H, Sugano S (2009) Design of human symbiotic robot TWENDY-ONE. In: IEEE international conference on robotics and automation, pp 580–586

  41. Ambady N, Weisbuch M (2010) Nonverbal behavior. Handbook of social psychology. Harvard University Press, New York, pp 464–497

    Google Scholar 

  42. Emery NJ (2000) The eyes have it: the neuroethology, function and evolution of social gaze. Neurosci Biobehav Rev 24(6):581–604

    Article  Google Scholar 

  43. Srinivasan V, Murphy R (2011) A survey of social gaze. Human–robot interaction (HRI). Lausanne, Switzerland, pp 253–254

  44. Todorov A (2008) Evaluating faces on trustworthiness: an extension of systems for recognition of emotions signaling approach/avoidance behaviors. Ann N Y Acad Sci 1124(1):208–224

    Article  Google Scholar 

  45. Delgado MR, Frank RH, Phelps EA (2005) Perceptions of moral character modulate the neural systems of reward during the trust game. Nat Neurosci 8(11):1611–1618

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rik van den Brule.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (doc 206 KB)

Rights and permissions

Reprints and permissions

About this article

Cite this article

van den Brule, R., Dotsch, R., Bijlstra, G. et al. Do Robot Performance and Behavioral Style affect Human Trust?. Int J of Soc Robotics 6, 519–531 (2014). https://doi.org/10.1007/s12369-014-0231-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12369-014-0231-5

Keywords

Navigation