Abstract
Research in social robotics is focused on the development of robots that can provide physical and cognitive support in a socially interactive way. Whilst some studies have previously investigated the importance of user characteristics (age, gender, education, robot familiarity, mood) in the acceptance of social robots as well as the influence a robot’s displayed emotion (positive, negative, neutral) has on the interaction, these two aspects are rarely combined. Therefore, this study attempts to highlight the need to consider the influence that both human and robot attributes can have on social robot acceptance. Eighty-six participants completed implicit and explicit measures of mood before viewing one of three video clips containing a positive, negative or neutral social robot (Pepper) followed by questionnaires on robot acceptance and perception. Gender and education were not associated with acceptance; however, several constructs of the acceptance questionnaire significantly correlated with age and mood. For example, those younger and those experiencing sadness or loneliness were more dependent on the opinions of others (as measured by the social influence construct of the acceptance questionnaire). This highlights the importance of mood in the introduction of social robots into vulnerable populations. Robot familiarity also correlated with robot acceptance with those more familiar finding the robot less useful and less enjoyable, this is important as robots become more prominent in society. Displayed robot emotion significantly influenced acceptance and perception with the positive robot appearing more childlike than the negative and neutral robot, and the neutral robot the least helpful. These findings emphasise the importance of both user and robot characteristics in the successful integration of social robots.
References
[1] A. Winfield, Robotics: A very short introduction, OUP Oxford, 201210.1093/actrade/9780199695980.001.0001Search in Google Scholar
[2] W. H. Organization, World report on ageing and health, World Health Organization, 2015Search in Google Scholar
[3] S. M. S. Khaksar, R. Khosla, M. T. Chu, F. S. Shahmehr, Service innovation using social robot to reduce social vulnerability among older people in residential care facilities, Technological Forecasting and Social Change, 2016, 113, 438–45310.1016/j.techfore.2016.07.009Search in Google Scholar
[4] P. Khosravi, A. Rezvani, A. Wiewiora, The impact of technology on older adults’ social isolation, Computers in Human Behavior, 2016, 63, 594–60310.1016/j.chb.2016.05.092Search in Google Scholar
[5] D. Feil-Seifer, M. J. Mataric, Defining socially assistive robotics, In: 9th International Conference on Rehabilitation Robotics (ICORR 2005), IEEE, 2005, 465–468Search in Google Scholar
[6] M. M. de Graaf, S. B. Allouch, J. van Dijk, What makes robots social?: A user’s perspective on characteristics for social human-robot interaction, In: International Conference on Social Robotics, Springer, 2015, 184–19310.1007/978-3-319-25554-5_19Search in Google Scholar
[7] H. Robinson, B. MacDonald, E. Broadbent, The role of healthcare robots for older people at home: A review, International Journal of Social Robotics, 2014, 6(4), 575–59110.1007/s12369-014-0242-2Search in Google Scholar
[8] S. M. Rabbitt, A. E. Kazdin, B. Scassellati, Integrating socially assistive robotics into mental healthcare interventions: Applications and recommendations for expanded use, Clinical Psychology Review, 2015, 35, 35–4610.1016/j.cpr.2014.07.001Search in Google Scholar PubMed
[9] N. Ezer, A. D. Fisk, W. A. Rogers, Attitudinal and intentional acceptance of domestic robots by younger and older adults, In: International Conference on Universal Access in Human-Computer Interaction, Springer, 2009, 39–4810.1007/978-3-642-02710-9_5Search in Google Scholar PubMed PubMed Central
[10] C.-A. Smarr, et al., Domestic robots for older adults: attitudes, preferences, and potential, International Journal of Social Robotics, 2014, 6(2), 229–24710.1007/s12369-013-0220-0Search in Google Scholar PubMed PubMed Central
[11] J. M. Beer, A. Prakash, T. L. Mitzner, W. A. Rogers, Understanding robot acceptance, Technical report, Georgia Institute of Technology, 2011Search in Google Scholar
[12] V. Venkatesh, M. G. Morris, G. B. Davis, F. D. Davis, User acceptance of information technology: Toward a unified view. MIS Quarterly, 2003, 425–47810.2307/30036540Search in Google Scholar
[13] I. Gaudiello, E. Zibetti, S. Lefort, M. Chetouani, S. Ivaldi, Trust as indicator of robot functional and social acceptance, An experimental study on user conformation to iCub answers, Computers in Human Behavior, 2016, 61, 633–65510.1016/j.chb.2016.03.057Search in Google Scholar
[14] M. Heerink, B. Kröse, V. Evers, B. Wielinga, Assessing acceptance of assistive social agent technology by older adults: the Almere model, International Journal of Social Robotics, 2010, 2(4), 361–37510.1007/s12369-010-0068-5Search in Google Scholar
[15] M. Heerink, Exploring the influence of age, gender, education and computer experience on robot acceptance by older adults, In: Proceedings of the 6th International Conference on Human-Robot Interaction, ACM, 2011, 147–14810.1145/1957656.1957704Search in Google Scholar
[16] I. H. Kuo, et al., Age and gender factors in user acceptance of healthcare robots, In: 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (ROMAN), IEEE, 2009, 214–219Search in Google Scholar
[17] M. M. De Graaf, S. B. Allouch, Exploring influencing variables for the acceptance of social robots, Robotics and Autonomous Systems, 2013, 61(12), 1476–148610.1016/j.robot.2013.07.007Search in Google Scholar
[18] K. O. Arras, D. Cerqui, Do we want to share our lives and bodies with robots? A 2000-people survey, Technical Report, 2005Search in Google Scholar
[19] A. Weiss, C. Bartneck, Meta analysis of the usage of the Godspeed Questionnaire Series, In: RO-MAN 2015 – The 24th IEEE International Symposium on Robot and Human Interactive Communication, IEEE, 2015, 381–38810.1109/ROMAN.2015.7333568Search in Google Scholar
[20] N. Schwarz, G. L. Clore, Mood, misattribution, and judgments of well-being: informative and directive functions of affective states, Journal of personality and social psychology, 1983, 45(3), 513–52310.1037/0022-3514.45.3.513Search in Google Scholar
[21] S. Baisch, T. Kolling, M. Knopf, Factors impacting on older and younger peoples’ perceptions of elderly robot users, Innovation in Aging, 2017, Suppl 1, 1190–119010.1093/geroni/igx004.4332Search in Google Scholar
[22] I. Blanchette, A. Richards, The influence of affect on higher level cognition: A review of research on interpretation, judgement, decision making and reasoning, Cognition and Emotion, 2010, 24(4), 561–59510.1080/02699930903132496Search in Google Scholar
[23] C. Beedie, P. Terry, A. Lane, Distinctions between emotion and mood, Cognition and Emotion, 2005, 19(6), 847–87810.1080/02699930541000057Search in Google Scholar
[24] D. Watson, L. A. Clark, A. Tellegen, Development and validation of brief measures of positive and negative affect: the PANAS scales, Journal of personality and social psychology, 1988, 54(6), 1063–107010.1037/0022-3514.54.6.1063Search in Google Scholar
[25] D. Watson, L. A. Clark, The PANAS-X: Manual for the positive and negative affect schedule-expanded form, Iowa Research Online, 1999Search in Google Scholar
[26] M. Quirin, M. Kazén, J. Kuhl, When nonsense sounds happy or helpless: the implicit positive and negative affect test (IPANAT), Journal of Personality and Social Psychology, 2009, 97(3), 500–51610.1037/a0016063Search in Google Scholar PubMed
[27] D. Keltner, J. Haidt, Social functions of emotions at four levels of analysis, Cognition and Emotion, 1999, 13(5), 505–52110.1080/026999399379168Search in Google Scholar
[28] E. A. Butler, B. Egloff, F. H. Wlhelm, N. C. Smith, E. A. Erickson, J. J. Gross, The social consequences of expressive suppression, Emotion, 2003, 3(1), 48–6710.1037/1528-3542.3.1.48Search in Google Scholar
[29] S. Brave, C. Nass, K. Hutchinson, Computers that care: investigating the effects of orientation of emotion exhibited by an embodied computer agent, International Journal of Human-Computer Studies, 2005, 62(2), 161–17810.1016/j.ijhcs.2004.11.002Search in Google Scholar
[30] I. Leite, A. Pereira, S. Mascarenhas, C. Martinho, R. Prada, A. Paiva, The influence of empathy in human-robot relations, International Journal of Human-Computer Studies, 2013, 71(3), 250–26010.1016/j.ijhcs.2012.09.005Search in Google Scholar
[31] A. Paiva, I. Leite, H. Boukricha, I. Wachsmuth, Empathy in virtual agents and robots: a survey, ACM Transactions on Interactive Intelligent Systems (TiiS), 2017, 7(3), Article 1110.1145/2912150Search in Google Scholar
[32] S. Chumkamon, E. Hayashi, M. Koike, Intelligent emotion and behavior based on topological consciousness and adaptive resonance theory in a companion robot, Biologically Inspired Cognitive Architectures, 2016, 18, 51–6710.1016/j.bica.2016.09.004Search in Google Scholar
[33] A. Dijksterhuis, J. A. Bargh, The perception-behavior express-way: Automatic effects of social perception on social behaviour, In: M. P. Zanna (Ed.), Advances in Experimental Social Psychology, San Diego, CA, US: Academic Press, 2001, 33, 1–4010.1016/S0065-2601(01)80003-4Search in Google Scholar
[34] M. R. Banaji, C. Hardin, A. J. Rothman, Implicit stereotyping in person judgment, Journal of Personality and Social Psychology, 1993, 65(2), 272–28110.1037/0022-3514.65.2.272Search in Google Scholar
[35] M. L. Walters, The design space for robot appearance and behaviour for social robot companions, Ph.D. thesis, 2008Search in Google Scholar
[36] J. Goetz, S. Kiesler, Cooperation with a robotic assistant, In: CHI’02 Extended Abstracts on Human Factors in Computing Systems (ACM, 2002) 578–57910.1145/506443.506492Search in Google Scholar
[37] J. Goetz, S. Kiesler, A. Powers, Matching robot appearance and behavior to tasks to improve human-robot cooperation, In: Proceedings of the 12th IEEE International Workshop on Robot and Human Interactive Communication, IEEE Press Piscataway, NJ, 2003, 55–60Search in Google Scholar
[38] B. R. Duffy, Anthropomorphism and the social robot, Robotics and autonomous systems, 2003, 42(3-4), 177–19010.1016/S0921-8890(02)00374-3Search in Google Scholar
[39] C. Bartneck, D. Kulić, E. Croft, S. Zoghbi, Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots, International Journal of Social Robotics, 2009, 1(1), 71–8110.1007/s12369-008-0001-3Search in Google Scholar
[40] M. Mori, The uncanny valley, Energy, 1970, 7(4), 33–35Search in Google Scholar
[41] S. Baisch, et al., Acceptance of social robots by elder people: does psychosocial functioning matter?, International Journal of Social Robotics, 2017, 9(2), 293–30710.1007/s12369-016-0392-5Search in Google Scholar
[42] A. Beck, et al., Interpretation of emotional body language displayed by a humanoid robot: A case study with children, International Journal of Social Robotics, 2013, 5(3), 325–33410.1007/s12369-013-0193-zSearch in Google Scholar
[43] D.-S. Kwon, et al., Emotion interaction system for a service robot, In: RO-MAN 2007 – The 16th IEEE International Symposium on Robot and Human Interactive Communication, IEEE, 2007, 351–356Search in Google Scholar
[44] A. van Maris, N. Zook, P. Caleb-Solly, M. Studley, A. Winfield, S. Dogramadzi, Ethical considerations of (contextually) affective robot behaviour, (forthcoming)Search in Google Scholar
[45] K. R. Scherer, What are emotions? And how can they be measured?, Social Science Information, 2005, 44(4), 695–72910.1177/0539018405058216Search in Google Scholar
© 2019 Laura Bishop et al., published by De Gruyter
This work is licensed under the Creative Commons Attribution 4.0 Public License.
