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Article published In:
Envisioning Social Robotics: Current challenges and new interdisciplinary methodologies
Edited by Glenda Hannibal and Astrid Weiss
[Interaction Studies 21:1] 2020
► pp. 24–56

Towards a new scale for assessing attitudes towards social robots

The attitudes towards social robots scale (ASOR)

| Aarhus University
| Aarhus University
| Aarhus University
| University of Helsinki
| Aarhus University
| Aarhus University

Background: The surge in the development of social robots gives rise to an increased need for systematic methods of assessing attitudes towards robots.

Aim: This study presents the development of a questionnaire for assessing attitudinal stance towards social robots: the ASOR.

Methods: The 37-item ASOR questionnaire was developed by a task-force with members from different disciplines. It was founded on theoretical considerations of how social robots could influence five different aspects of relatedness.

Results: Three hundred thirty-nine people responded to the survey. Factor analysis of the ASOR yielded a three-factor solution consisting of a total of 25 items: “ascription of mental capacities”, “ascription of socio-practical capacities”, and “ascription of socio-moral status”. This data was further triangulated with data from interviews (n = 10).

Conclusion: the ASOR allows for assessment of three distinct facets of ascription of capacities to social robots and offers a new type of assessment of attitudes towards social robots. It appeared that ASOR not only assesses ascription of capacities to social robots but it also gauged overall positive attitudes towards social robots.

Keywords: Human Robot Interaction (HRI), attitudes towards social robots, methodologies in HRI
Article outline
  • Introduction
  • Methods
    • Development of the attitudes towards social robots scale (ASOR)
    • Procedure
      • Online piloting
      • Focus group
      • Clinical sample
      • Distribution of ASOR to larger sample
      • Qualitative semi-structured research interviews
    • Measures
    • The robot
    • Statistics
      • Preliminary factor analysis
    • Qualitative data
  • Discussion
    • Limitations and future directions
    • Conflict of interest
  • References
Published online: 24 January 2020
DOI logo
https://doi.org/10.1075/is.18055.fle
References
Arras, K. O., & Cerqui, D.
(2005) Do we want to share our lives and bodies with robots? A 2000 people survey. Retrieved from [URL]
Atkinson, P.
(1992) Understanding ethnographic texts (Vol. 251). Sage Publications, Inc.. DOI logoGoogle Scholar
Bainbridge, W. A., Hart, J. W., Kim, E. S., & Scassellati, B.
(2011) The Benefits of Interactions with Physically Present Robots over Video-Displayed Agents. International Journal of Social Robotics, 3(1), 41–52. DOI logoGoogle Scholar
Barbour, R.
(2008) Doing focus groups. Sage.Google Scholar
Baron, N. S.
(2004) See you online: Gender issues in college student use of instant messaging. Journal of Language and Social Psychology, 23(4), 397–423. DOI logoGoogle Scholar
Bartneck, C., Kulić, D., Croft, E., & Zoghbi, S.
(2009) Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. International Journal of Social Robotics, 1(1), 71–81. DOI logoGoogle Scholar
Briggs, S. R., & Cheek, J. M.
(1986) The role of factor analysis in the development and evaluation of personality scales. Journal of Personality, 54(1), 106–148. DOI logoGoogle Scholar
Brinkmann, S., & Kvale, S.
(2015) Interviews learning the craft of qualitative research interviews 3rd Edition. Sage. Brandon, J. and Davies, M. (1979). The Limits of Competence in Social Work: The Assessment of Marginal Students in Social Work Education. British Journal of Social Work, 9(3), 295–347.Google Scholar
Brinkmann, Svend, & Tanggaard, L.
(2010) Kvalitative metoder: en grundbog. Hans Reitzels Forlag.Google Scholar
Broadbent, E., Orejana, J. R., Ahn, H. S., Xie, J., Rouse, P., & MacDonald, B. A.
(2015) The cost-effectiveness of a robot measuring vital signs in a rural medical practice. 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 577–581. IEEE. DOI logoGoogle Scholar
Broadbent, E., Tamagawa, R., Patience, A., Knock, B., Kerse, N., Day, K., & MacDonald, B. A.
(2012) Attitudes towards health-care robots in a retirement village. Australasian Journal on Ageing, 31(2), 115–120. DOI logoGoogle Scholar
Carnap, R.
(1988) Meaning and necessity: a study in semantics and modal logic. University of Chicago Press.Google Scholar
Cattell, R. B.
(1966) The scree test for the number of factors. Multivariate Behavioral Research, 1(2), 245–276. DOI logoGoogle Scholar
Daly, C.
(2010) An introduction to philosophical methods. Broadview Press.Google Scholar
Damholdt, Vestergaard C., & Seibt, J.
(2019) Testing for ‘Anthropomorphisation’ – A Case for Mixed Methods in HRI. Springer Publishing Co, New York, NY.Google Scholar
Damholdt, Yamazaki R., Hakli, R., Hansen, C. V., Vestergaard, C., & Seibt, J.
(2015) Attitudinal Change in Elderly Citizens Toward Social Robots: The Role of Personality Traits and Beliefs About Robot Functionality. Human-Media Interaction, 17011. DOI logoGoogle Scholar
Dautenhahn, K., Walters, M., Woods, S., Koay, K. L., Nehaniv, C. L., Sisbot, A., … Siméon, T.
(2006) How may I serve you?: a robot companion approaching a seated person in a helping context. Proceeding of the 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction – HRI ’06, 1721. DOI logoGoogle Scholar
Dautenhahn, K., Woods, S., Kaouri, C., Walters, M. L., Koay, K. L., & Werry, I.
(2005) What is a robot companion – friend, assistant or butler? 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 1192–1197. DOI logoGoogle Scholar
Derrick, B., & White, P.
(2016) Why Welch’s test is Type I error robust. The Quantitative Methods for Psychology, 12(1), 30–38. DOI logoGoogle Scholar
Dillman, D. A., Smyth, J. D., & Christian, L. M.
(2014) Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored Design Method, 4th Edition. John Wiley & Sons, Inc.Google Scholar
Duffy, B. R.
(2003) Anthropomorphism and the social robot. Robotics and Autonomous Systems, 42(3), 177–190. DOI logoGoogle Scholar
Ezer, N., Fisk, A. D., & Rogers, W. A.
(2009) Attitudinal and intentional acceptance of domestic robots by younger and older adults. In Universal Access in Human-Computer Interaction. Intelligent and Ubiquitous Interaction Environments (pp. 39–48). Retrieved from [URL]. DOI logo
Fink, J.
(2012) Anthropomorphism and human likeness in the design of robots and human-robot interaction. International Conference on Social Robotics, 199–208. Retrieved from [URL]. DOI logo
Garland, R.
(1991) The mid-point on a rating scale: Is it desirable. Marketing Bulletin, 66–70.Google Scholar
Gray, K., & Wegner, D. M.
(2009) Moral typecasting: divergent perceptions of moral agents and moral patients. Journal of Personality and Social Psychology, 96(3), 505. DOI logoGoogle Scholar
(2011) Morality takes two: Dyadic morality and mind perception. The Social Psychology of Morality: Exploring the Causes of Good and Evil 2011, 109–27.Google Scholar
Hammersley, M., & Atkinson, P.
(2007) Ethnography: Principles in practice. Routledge. DOI logoGoogle Scholar
Hardin, R.
(2002) Trust and trustworthiness. Retrieved from [URL]
Himma, K. E.
(2009) Artificial agency, consciousness, and the criteria for moral agency: What properties must an artificial agent have to be a moral agent? Ethics and Information Technology, 11(1), 19–29. DOI logoGoogle Scholar
Horn, J. L.
(1965) A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179–185. DOI logoGoogle Scholar
Johnson, J. A.
(2014) Measuring thirty facets of the Five Factor Model with a 120-item public domain inventory: Development of the IPIP-NEO-120. Journal of Research in Personality, 511, 78–89. DOI logoGoogle Scholar
Kahn, P. H., Reichert, A. L., Gary, H. E., Kanda, T., Ishiguro, H., Shen, S., … Gill, B.
(2011) The new ontological category hypothesis in human-robot interaction. Proceedings of the 6th International Conference on Human-Robot Interaction – HRI ’11, 1591. DOI logoGoogle Scholar
Kamide, H., Takubo, T., Ohara, K., Mae, Y., & Arai, T.
(2014) Impressions of humanoids: the development of a measure for evaluating a humanoid. International Journal of Social Robotics, 6(1), 33–44. DOI logoGoogle Scholar
Khan, Z.
(1998) Attitudes towards intelligent service robots. NADA KTH, Stockholm, 171. Retrieved from [URL]
Kim, J., Lee, H. Y., Candace Christensen, M., & Merighi, J. R.
(2017) Technology access and use, and their associations with social engagement among older adults: Do women and men differ? Journals of Gerontology – Series B Psychological Sciences and Social Sciences, 72(5), 836–845. DOI logoGoogle Scholar
Korsgaard, C.
(2004) Fellow creatures: Kantian ethics and our duties to animals.Google Scholar
Krátký, J., McGraw, J. J., Xygalatas, D., Mitkidis, P., & Reddish, P.
(2016) It Depends Who Is Watching You: 3-D Agent Cues Increase Fairness. PLOS ONE, 11(2), e0148845. DOI logoGoogle Scholar
Krosnick, J. A., Narayan, S., & Smith, W. R.
(1996) Satisficing in surveys: Initial evidence. New Directions for Evaluation 1996(70), 29–44. DOI logoGoogle Scholar
Kuo, I. H., Rabindran, J. M., Broadbent, E., Lee, Y. I., Kerse, N., Stafford, R. M. Q., & MacDonald, B. A.
(2009) Age and gender factors in user acceptance of healthcare robots. Robot and Human Interactive Communication, 2009. RO-MAN 2009. The 18th IEEE International Symposium On, 214–219. Retrieved from [URL]. DOI logo
Ledesma, R. D., & Valero-Mora, P.
(2007) Determining the number of factors to retain in EFA: An easy-to-use computer program for carrying out parallel analysis. Practical Assessment, Research & Evaluation, 12(2), 1–11.Google Scholar
Lee, K. M., Jung, Y., Kim, J., & Kim, S. R.
(2006) Are physically embodied social agents better than disembodied social agents?: The effects of physical embodiment, tactile interaction, and people’s loneliness in human–robot interaction. International Journal of Human-Computer Studies, 64(10), 962–973. DOI logoGoogle Scholar
Leung, S.-O.
(2011) A Comparison of Psychometric Properties and Normality in 4-, 5-, 6-, and 11-Point Likert Scales. Journal of Social Service Research, 37(4), 412–421. DOI logoGoogle Scholar
Louie, W.-Y. G., McColl, D., & Nejat, G.
(2014) Acceptance and attitudes toward a human-like socially assistive robot by older adults. Assistive Technology, 26(3), 140–150. DOI logoGoogle Scholar
Melson, G. F., Kahn Jr., P. H., Beck, A., Friedman, B., Roberts, T., Garrett, E., & Gill, B. T.
(2009) Children’s behavior toward and understanding of robotic and living dogs. Journal of Applied Developmental Psychology, 30(2), 92–102. DOI logoGoogle Scholar
Moser, S. Claus, & Kalton, G.
(1972) Survey methods in social investigation (2nd American ed). Retrieved from [URL]
Mutlu, B., Osman, S., Forlizzi, J., Hodgins, J., & Kiesler, S.
(2006) Task Structure and User Attributes as Elements of Human-Robot Interaction Design. ROMAN 2006 – The 15th IEEE International Symposium on Robot and Human Interactive Communication, 74–79. DOI logoGoogle Scholar
Nass, C., Fogg, B. J., & Moon, Y.
(1996) Can computers be teammates? International Journal of Human-Computer Studies, 45(6), 669–678. DOI logoGoogle Scholar
Nass, C. I., Lombard, M., Henriksen, L., & Steuer, J.
(1995) Anthropocentrism and computers. Behaviour & Information Technology, 14(4), 229–238. DOI logoGoogle Scholar
Nass, C., & Moon, Y.
(2000) Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56(1), 81–103. DOI logoGoogle Scholar
Neave, N., Jackson, R., Saxton, T., & Hönekopp, J.
(2015) The influence of anthropomorphic tendencies on human hoarding behaviours. Personality and Individual Differences, 721, 214–219. DOI logoGoogle Scholar
Neff, K. D.
(2003) The Development and Validation of a Scale to Measure Self-Compassion. Self and Identity, 2(3), 223–250. DOI logoGoogle Scholar
Nomura, T., Kanda, T., & Suzuki, T.
(2006) Experimental investigation into influence of negative attitudes toward robots on human–robot interaction. Ai & Society, 20(2), 138–150. DOI logoGoogle Scholar
Nomura, T., Kanda, T., Suzuki, T., & Kato, K.
(2008) Prediction of Human Behavior in Human–Robot Interaction Using Psychological Scales for Anxiety and Negative Attitudes Toward Robots. Robotics, IEEE Transactions On, 24(2), 442–451. DOI logoGoogle Scholar
Nomura, T., Suzuki, T., Kanda, T., & Kato, K.
(2006a) Measurement of anxiety toward robots. Robot and Human Interactive Communication, 2006. ROMAN 2006. The 15th IEEE International Symposium On, 372–377. Retrieved from [URL]. DOI logo
(2006b) Measurement of negative attitudes toward robots. Interaction Studies, 7(3), 437–454. DOI logoGoogle Scholar
O’Connor, B. P.
(2000) SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior Research Methods, 32(3), 396–402.Google Scholar
Ogawa, K., Nishio, S., Koda, K., Taura, K., Minato, T., Ishii, C. T., & Ishiguro, H.
(2011) Telenoid: Tele-presence android for communication. ACM SIGGRAPH 2011 Emerging Technologies, 151. Retrieved from [URL]. DOI logo
Poland, B. D.
(2002) Transcription quality. In J. F. Gubrium & J. A. Holstein (Eds.), From the individual interview to the interview society. SAGE.Google Scholar
Public attitudes towards robots. Special Eurobarometer 382
(2012) Retrieved from [URL]
Rocks, C., Jenkins, S., Studley, M., & McGoran, D.
(2009) Heart robot: a public engagement project. Interaction Studies, 101, 427–452. DOI logoGoogle Scholar
Rodogno
(2015) Attachment and Moral Psychology. In J. Seibt & J. Garsdal (Eds.), Foundational Research on Values, Conflicts, and Intercultural Thought. Ontos Verlag/De Gruyter.Google Scholar
Ruxton, G. D.
(2006) Forum: The unequal variance t-test is an underused alternative to Student’s t-test and the Mann-Whitney U test. Behavioral Ecology, 17(4), 688–690. DOI logoGoogle Scholar
Saldaña, J.
(2009) The coding manual for qualitative researchers. Los Angeles, Calif: Sage.Google Scholar
Schermerhorn, P., Scheutz, M., & Crowell, C. R.
(2008) Robot social presence and gender: Do females view robots differently than males? 2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI), 263–270. DOI logoGoogle Scholar
Schuman, H., & Presser, S.
(1996) Questions and Answers in Attitude Surveys: Experiments on Question Form, Wording, and Context. SAGE.Google Scholar
Seibt, J., & Vestergaard, C.
(2018) Fair Proxy Communication: Using Social Robots to Modify the Mechanisms of Implicit Social Cognition. Research Ideas and Outcomes, 41, e31827. DOI logoGoogle Scholar
Simon, S. J., & Peppas, S. C.
(2005) Attitudes towards product website design: A study of the effects of gender. Journal of Marketing Communications, 11(2), 129–144. DOI logoGoogle Scholar
Singer, P.
(1995) Animal liberation. Random House.Google Scholar
Smedegaard, C. V.
(n.d.). Reframing the Role of Novelty within Social HRI: from Noise to Information. In Press 2019, (14th annual ACM/IEEE International Conference on Human-Robot Interaction). DOI logo
Spreng, R. N., McKinnon, M. C., Mar, R. A., & Levine, B.
(2009) The Toronto Empathy Questionnaire. Journal of Personality Assessment, 91(1), 62–71. DOI logoGoogle Scholar
Tung, F.-W.
(2011) Influence of Gender and Age on the Attitudes of Children towards Humanoid Robots. Human-Computer Interaction. Users and Applications, 637–646. DOI logoGoogle Scholar
Turkle, S.
(2011) Alone together. New York: Basic Books.Google Scholar
Vaughan, G., & Hogg, M. A.
(2005) Introduction to social psychology. Retrieved from [URL]
Waytz, A., Cacioppo, J., & Epley, N.
(2010) Who Sees Human? The Stability and Importance of Individual Differences in Anthropomorphism. Perspectives on Psychological Science, 5(3), 219–232. DOI logoGoogle Scholar
Weiss, A., Bernhaupt, R., Lankes, M., & Tscheligi, M.
(2009) The USUS Evaluation Framework for Human-Robot Interaction.Google Scholar
Złotowski, J., Sumioka, H., Eyssel, F., Nishio, S., Bartneck, C., & Ishiguro, H.
(2018) Model of Dual Anthropomorphism: The Relationship Between the Media Equation Effect and Implicit Anthropomorphism. International Journal of Social Robotics, 10(5), 701–714. DOI logoGoogle Scholar
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