Skip to main content
Log in

When a Robot’s Group Membership Matters

Anthropomorphization of Robots as a Function of Social Categorization

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

Abstract

Previous work has documented that humans categorize robots as members of different social groups, thereby using socially relevant cues such as a robot’s alleged gender or nationality. Importantly, these social categorization processes affect impressions people form about robots. In an experiment with N=45 participants, we utilized a minimal-group paradigm and tested whether categorizing the humanoid robot NAO as an in-group member vs. an out-group member based on socially non-relevant features would result in higher levels of anthropomorphism and more positive evaluations of the robot. Innovatively, to assess anthropomorphism, we utilized an implicit measurement procedure. Results support our hypotheses: Perceived in-group membership with the robot resulted in a greater extent of anthropomorphic inferences about the robot and more positive evaluations. Moreover, compared to the out-group condition, participants who perceived NAO as an in-group member showed greater willingness to interact with robots in general.

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

Similar content being viewed by others

Notes

  1. The original measure consisted of 10 items. However, four traits (hard-hearted, shallow, rude, cold) substantially reduced the reliability of the measure (α=.76) and thus were excluded from the overall index.

  2. Before accumulating all RTs, some extreme, implausible long RTs (i.e., RTs up to 15774 ms) were detected that would have disproportionately boosted the overall RT mean and standard deviation. Therefore, RTs were z-transformed. Cases with standardized scores in excess of z=3.29 (RTs ranging between 2564 ms and 15774 ms; 1,8 %) were considered as an outlier and discarded from the data set. All reported data preparation and data analyses are based on the data set excluding these extreme values.

References

  1. Eyssel F, Kuchenbrandt D (2012) Social categorization of social robots: antropomorphism as a function of robot group membership. Brit J Soc Psychol 51:724–731

    Article  Google Scholar 

  2. Eyssel F, Kuchenbrandt D, Bobinger S (2011) Effects of anticipated human-robot interaction and predictability of robot behavior on perceptions of anthropomorphism. In: Proc of the 6th HRI int conf on hum-robot interact (HRI 2011), pp 61–67

    Chapter  Google Scholar 

  3. Eyssel F, Kuchenbrandt D (2011) Manipulating anthropomorphic inferences about NAO: the role of situational and dispositional aspects of effectance motivation. In: Proc of the 20th IEEE int symp in robot and hum interact commun (RO-MAN 2011), pp 467–472

    Google Scholar 

  4. Nass C, Fogg BJ, Moon Y (1996) Can computers be teammates? Int J Hum-Comput Stud 45:669–678

    Article  Google Scholar 

  5. Nass C, Moon Y (2000) Machines and mindlessness: social responses to computers. J Soc Issues 56:81–103

    Article  Google Scholar 

  6. Nass C, Steuer JS, Tauber E (1994) Computers are social actors. In: Proc of the CHI conf, pp 72–77

    Google Scholar 

  7. Riether N, Hegel F, Wrede B, Horstmann G (2012) Social facilitation with social robots? In: Proc of the 7th ACM/IEEE conf hum-robot interact (HRI 2012), pp 41–48

    Google Scholar 

  8. Zajonc RB (1965) Social facilitation. Science 149:269–274

    Article  Google Scholar 

  9. Gray HM, Gray K, Wegner DM (2007) Dimensions of mind perception. Science 315:619

    Article  Google Scholar 

  10. Waytz A, Epley N, Cacioppo JT (2010) Social cognition unbound: insights into anthropomorphism and dehumanization. Curr Dir Psychol Sci 19:58–62

    Article  Google Scholar 

  11. Epley N, Waytz A, Cacioppo JT (2007) On seeing human: a three-factor theory of anthropomorphism. Psychol Rev 114:864–886

    Article  Google Scholar 

  12. Waytz A, Morewedge CK, Epley N, Monteleone G, Gao J, Cacioppo JT (2010) Making sense by making sentient: effectance motivation increases anthropomorphism. J Pers Soc Psychol 3:410–435. doi:10.1037/a0020240

    Google Scholar 

  13. Luczak H, Rötting M, Schmidt L (2003) Let’s talk: anthropomorphization as a means to cope with stress of interacting with technical devices. Ergonomics 46:1361–1374

    Article  Google Scholar 

  14. Eyssel F, Hegel F, Horstmann G, Wagner C (2010) Anthropomorphic inferences from emotional nonverbal cues: a case study. In: Proc of the 19th IEEE int symp in robot and hum interact commun (RO-MAN 2010), pp 681–686

    Google Scholar 

  15. Eyssel F, Hegel F (2012) (S)he’s got the look: gender-stereotyping of social robots. J Appl Soc Psychol 42:2213–2230

    Article  Google Scholar 

  16. Hegel F, Eyssel F, Wrede B (2010) The social robot flobi: key concepts of industrial design. In: Proc of the 19th IEEE int symp in robot and hum interact commun (RO-MAN 2010), pp 120–125

    Google Scholar 

  17. Morewedge CK, Preston J, Wegner DM (2007) Timescale bias in the attribution of mind. J Pers Soc Psychol 93:1–11

    Article  Google Scholar 

  18. Eyssel F, Kuchenbrandt D, Bobinger S, de Ruiter L, Hegel F (2012) ‘If you sound like me, you must be more human’: on the interplay of robot and user features on human-robot acceptance and anthropomorphism. In: Proc of the 7th ACM/IEEE conf on hum-robot interact, pp 125–126

    Google Scholar 

  19. Duffy BR (2003) Anthropomorphism and the social robot. Robot Auton Syst 42:170–190. doi:10.1016/S0921-8890(02)00374-3

    Article  Google Scholar 

  20. Duffy BR (2008) Fundamental issues in affective intelligent social machines. Open Artif Intell J 2:21–34

    Article  Google Scholar 

  21. Tajfel H, Turner JC (1979) An integrative theory of intergroup conflict. In: Austin WG, Worchel S (eds) The social psychology of intergroup relations. Brooks/Cole, Oxford, pp 33–47

    Google Scholar 

  22. Gaertner SL, Dovidio JF (2000) Reducing intergroup bias: the common ingroup identity model. Psychol Press, New York

    Google Scholar 

  23. Jackson LA, Hodge CN, Gerard DA, Ingram JM, Ervin KS, Sheppard LA (1996) Cognition, affect, and behavior in the prediction of group attitudes. Pers Soc Psychol Bull 22:306–316

    Article  Google Scholar 

  24. Tajfel H, Billig MG, Bundy RP, Flament C (1971) Social categorization and intergroup behavior. Eur J Soc Psychol 1:149–178

    Article  Google Scholar 

  25. Haslam N (2006) Dehumanization: an integrative review. Pers Soc Psychol Rev 10:252–264

    Article  Google Scholar 

  26. Leyens J-P, Paladino MP, Rodríguez-Torres R, Vaes J, Demoulin S, Rodríguez-Pérez A et al (2000) The emotional side of prejudice: the attribution of secondary emotions to ingroups and outgroups. Pers Soc Psychol Rev 4:186–197

    Article  Google Scholar 

  27. Leyens JPh, Rodriguez AP, Rodriguez RT, Gaunt R, Paladino PM, Vaes J, Demoulin S (2001) Psychological essentialism and the attribution of uniquely human emotions to ingroups and outgroups. Eur J Soc Psychol 31:395–411

    Article  Google Scholar 

  28. Nass C, Isbister K, Lee E-J (2000) Truth is beauty: researching embodied conversational agents. In: Cassells J (ed) Embodied conversational agents. MIT Press, Cambridge, pp 374–402

    Google Scholar 

  29. Banaji MR, Greenwald AG (1994) Implicit stereotyping and prejudice. In: Zanna MP, Olson JM (eds) The psychology of prejudice: the Ontario symposium, vol 7. Erlbaum, Hillsdale, pp 55–76

    Google Scholar 

  30. Greenwald AG, Banaji MR (1995) Implicit social cognition: attitudes, self-esteem, and stereotypes. Psychol Rev 102:4–27

    Article  Google Scholar 

  31. Fazio RH, Jackson JR, Dunton BC, Williams CJ (1995) Variability in automatic activation as an unobtrusive measure of racial attitudes: a bona fide pipeline? J Pers Soc Psychol 69:1013–1027

    Article  Google Scholar 

  32. Greenwald AG, McGhee DE, Schwartz JKL (1998) Measuring individual differences in implicit cognition: the implicit association test. J Pers Soc Psychol 74:1464–1480

    Article  Google Scholar 

  33. De Houwer J, Teige-Mocigemba S, Spruyt A, Moors A (2009) Implicit measures: a normative analysis and review. Psychol Bull 135:347–368

    Article  Google Scholar 

  34. Wentura D, Degner J (2010) A practical guide to sequential priming and related tasks. In: Gawronski B, Payne BK (eds) Handbook of implicit social cognition: measurement, theory, and applications. Guilford Press, New York, pp 95–116

    Google Scholar 

  35. Collins AM, Loftus EF (1975) A spreading activation theory of semantic processing. Psychol Rev 82:407–428

    Article  Google Scholar 

  36. Rydell RJ, McConnell AR (2010) Consistency and inconsistency in implicit social cognition: the case of implicit and explicit measures of attitudes. In: Gawronski B, Payne BK (eds) Handbook of implicit social cognition: measurement, theory, and applications. Guilford Press, New York, pp 295–310

    Google Scholar 

  37. Payne BK, Burkley M, Stokes MB (2008) Why do implicit and explicit attitude tests diverge? The role of structural fit. J Pers Soc Psychol 94:16–31

    Article  Google Scholar 

  38. Goette L, Huffman D, Meier S (2006) The impact of group membership on cooperation and norm enforcement: evidence using random assignment to real social groups. Am Econ Rev 96:212–216

    Article  Google Scholar 

  39. Dovidio JF, Kawakami K, Gaertner SL (2002) Implicit and explicit prejudice and interracial interaction. J Pers Soc Psychol 82:62–68

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dieta Kuchenbrandt.

Appendix

Appendix

Primary emotions::

Excitement, joy, surprise, happiness, pleasure, anxiety, fear, pain, sadness, anger

Secondary emotions::

Love, hope, passion, emotion, admiration, contempt, guilt, shame, bitterness, spitefulness

Distractor words::

Car, tree, concrete, letterpress, sidewalk, butter, ticket, shutter, figure, terrain, autumn, mall, pebble, lampshades, lineal, mobile phone, stake, postcard, sailboat, track, door, bird, water, fence.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kuchenbrandt, D., Eyssel, F., Bobinger, S. et al. When a Robot’s Group Membership Matters. Int J of Soc Robotics 5, 409–417 (2013). https://doi.org/10.1007/s12369-013-0197-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12369-013-0197-8

Keywords

Navigation