Abstract
Recent studies on human–robot interactions have suggested that humanoid robots have considerable potential in social cognition research. However, the authors are not aware of any studies regarding social information processing from human–robot interactions. To address this issue, we considered two types of social interaction tasks (initiating and responding joint attention tasks) and two types of interaction partners (robot and human partners). Distinguishing between these types of joint attention (JA) is important, because they are thought to reflect unique but common constellations of processes in human social cognition and social learning. Thirty-seven participants were recruited (Study 1: 20 participants, Study 2: 17 participants) for the current study, and they conducted a picture recognition social information processing task with either robot or human partners. The results of Study 1 suggested that participants who interacted with a humanoid robot achieved a better recognition memory performance in the initiating JA condition than in the responding JA condition. The results of Study 2 suggested that the human–human and human–robot interactions resulted in no quantifiable differences in recognition memory. We discuss the implications of our results for the utility of humanoid robots in social cognition studies and future research questions on human–robot interactions.
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References
Chaminade T, Cheng G (2009) Social cognitive neuroscience and humanoid robotics. J Physiol Paris 103(3):286–295
Bluethmann W, Ambrose R, Diftler M, Askew S, Huber E, Goza M, Rehnmard F, Lovchik C, Magruder D (2003) Robonaut: a robot designed to work with humans in space. Auton Robot 14(2–3):179–197
Fasola J, Matarić MJ (2012) Using socially assistive human–robot interaction to motivate physical exercise for older adults. P IEEE 100(8):2512–2526
Marti P, Bacigalupo M, Giusti L, Mennecozzi C, Shibata T (2006) Socially assistive robotics in the treatment of behavioural and psychological symptoms of dementia. In: The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006, BioRob, pp 483–488
Tapus A, Mataric MJ, Scasselati B (2007) Socially assistive robotics [Grand challenges of robotics]. IEEE Robot Autom Mag 14(1):35–42
Anzalone SM, Tilmont E, Boucenna S, Xavier J, Jouen AL, Bodeau N, Maharatna K, Cehtouani M, Cohen D (2014) How children with autism spectrum disorder behave and explore the 4-dimensional (spatial 3D+ time) environment during a joint attention induction task with a robot. Res Autism Spect Dis 8(7):814–826
Fiske ST, Taylor SE (2013) Social cognition: from brains to culture. Sage, California
Horan WP, Kern RS, Green MF, Penn DL (2008) Social cognition training for individuals with schizophrenia: emerging evidence. Am J Psychiatr Rehabil 11(3):205–252
Lewis M (2012) Social cognition and the acquisition of self. Springer, Heidelberg
Burns JK (2006) Psychosis: a costly by-product of social brain evolution in Homo sapiens. Prog Neuro Psychopharmacol 30(5):797–814
Premack D, Woodruff G (1978) Does the chimpanzee have a theory of mind? Behav Brain Sci 1(4):515–526
Robins B, Dautenhahn K, Te Boekhorst R, Billard A (2005) Robotic assistants in therapy and education of children with autism: can a small humanoid robot help encourage social interaction skills? Univ Access Inf 4(2):105–120
Chaminade T, Okka MM (2013) Comparing the effect of humanoid and human face for the spatial orientation of attention. Front Neurorobot 7(12):1–7
Pierno AC, Mari M, Lusher D, Castiello U (2008) Robotic movement elicits visuomotor priming in children with autism. Neuropsychologia 46(2):448–454
Duquette A, Michaud F, Mercier H (2008) Exploring the use of a mobile robot as an imitation agent with children with low-functioning autism. Auton Robot 24(2):147–157
Bisio A, Sciutti A, Nori F, Metta G, Fadiga L, Sandini G, Pozzo T (2014) Motor contagion during human–human and human–robot interaction. PLoS ONE 9(8):1–10
Imai M, Ono T, Ishiguro H (2003) Physical relation and expression: joint attention for human–robot interaction. IEEE Trans Ind Electron 50(4):636–643
Skantze H, Hjalmarsson A, Oertel C (2014) Turn-taking, feedback and joint attention in situated human–robot interaction. Speech Commun 65:50–66
Johansson M, Skantze G, Gustafson J (2013) Head pose patterns in multiparty human-robot team-building interactions. In: International conference on social robotics, pp 351–360
Baldwin MW (1995) Relational schemas and cognition in close relationships. J Soc Pers Relat 12(4):547–552
Mundy P, Sullivan L, Mastergeorge AM (2009) A parallel and distributed-processing model of joint attention, social cognition and autism. Autism Res 2(1):2–21
Kasari C, Paparella T, Freeman S, Jahromi LB (2008) Language outcome in autism: randomized comparison of joint attention and play interventions. J Consult Clin Psychol 76(1):125–137
Tomasello M, Carpenter M, Call J, Behne T, Moll H (2005a) Understanding and sharing intentions: the origins of cultural cognition. Behav Brain Sci 28(5):675–691
Tomasello M, Carpenter M, Hobson RP (2005b) The emergence of social cognition in three young chimpanzees. Monogr Soc Res Child 70(1):1–152
Baron-Cohen S (1997) Mindblindness: an essay on autism and theory of mind. MIT Press, Cambridge
Seibert JM, Hogan AE, Mundy PC (1982) Assessing interactional competencies: The early social-communication scales. Infant Ment Health J 3(4):244–258
Redcay E, Dodell-Feder D, Pearrow MJ, Mavros PL, Kleiner M, Gabrieli JD, Saxe R (2010) Live face-to-face interaction during fMRI: a new tool for social cognitive neuroscience. Neuroimage 50(4):1639–1647
Schilbach L, Wilms M, Eickhoff SB, Romanzetti S, Tepest R, Bente G, Shah NJ, Fink GR, Vogeley K (2010) Minds made for sharing: initiating joint attention recruits reward-related neurocircuitry. J Cogn Neurosci 22(12):2702–2715
Kim K, Mundy P (2012) Joint attention, social-cognition, and recognition memory in adults. Front Hum Neurosci 6(172):1–11
Ricks DJ, Colton MB (2010) Trends and considerations in robot-assisted autism therapy. In: 2010 IEEE international conference on robotics and automation (ICRA), pp 4354–4359
Scassellati B (2007) How social robots will help us to diagnose, treat, and understand autism. In: Robotics research, pp 552–563. Springer, Berlin
Warren ZE, Zheng Z, Swanson AR, Bekele E, Zhang L, Crittendon JA, Weitlauf AF, Sarkar N (2013) Can robotic interaction improve joint attention skills? J Autism Dev Disord 45(11):3726–34
Dautenhahn K (2003) Roles and functions of robots in human society: implications from research in autism therapy. Robotica 21(4):443–452
Kaliouby RE (2005) Ming-reading machines: automated inference of complex mental States. University of Cambridge
Hadar U, Steiner TJ, Rose FC (1983) Head movement during listening turns in conversation. J Nonverbal Behav 9(4):214–228
Wallbott HG (1998) Bodily expression of emotion. Eur J Soc Psychol 28(6):879–896
Torta E, van Heumen J, Piunti F, Romeo L, Cuijpers R (2015) Evaluation of unimodal and multimodal communication cues for attracting attention in human–robot Interaction. Int J Soc Robot 7(1):89–96
Zheng Z, Zhang L, Bekele E, Swanson A, Crittendon JA, Warren Z, Sarkar N (2013) Impact of robot-mediated interaction system on joint attention skills for children with autism. In: 2013 IEEE international conference on rehabilitation robotics (ICORR), pp 1–8
Hall ET (1966) The hidden dimension. Doubleday, New York
Schulz KP, Fan J, Magidina O, Marks DJ, Hahn B, Halperin JM (2007) Does the emotional go/no-go task really measure behavioral inhibition?: convergence with measures on a non-emotional analog. Arch Clin Neuropsychol 22(2):151–160
Stanislaw H, Todorov N (1999) Calculation of signal detection theory measures. Behav Res Method Intrum C 31(1):137–149
Sheslow D, Adams W (2003) Wide range assessment of memory and learning-revised (WRAML-2). Administration and Technical Manual. Wide Range. Inc., Wilmington
Watson D, Friend R (1969) Measurement of social-evaluative anxiety. J Consult Clin Psych 33(4):448–457
Bandura A (1977) Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev 84(2):191–215
Vygotsky L (1978) Interaction between learning and development. Read Dev Child 23(3):34–41
Brooks R, Meltzoff AN (2002) The importance of eyes: how infants interpret adult looking behavior. Dev Psychol 38(6):958
Mundy P, Newell L (2007) Attention, joint attention, and social cognition. Curr Dir Psychol Sci 16(5):269–274
Mundy P, Card J, Fox N (2000) EEG correlates of the development of infant joint attention skills. Dev Psychobiol 36(4):325
Larsen RJ, Shackelford TK (1996) Gaze avoidance: personality and social judgments of people who avoid direct face-to-face contact. Pers Indiv Differ 21(6):907–917
Won AS, Perone B, Friend M, Bailenson JN (2016) Identifying Anxiety Through Tracked Head Movements in a Virtual Classroom. Cyberpsychol Behav Soc Netw 19(6):380–387
Eagly AH (1983) Gender and social influence: a social psychological analysis. Am Psychol 38(9):971–981
Tay B, Jung Y, Park T (2014) When stereotypes meet robots: the double-edge sword of robot gender and personality in human–robot interaction. Comput Hum Behav 38:75–84
Siegel M, Breazeal C, Norton MI (2009) Persuasive robotics: the influence of robot gender on human behavior. In: 2009 IEEE/RSJ international conference on intelligent robots and systems (IROS), pp 2563–2568
Acknowledgements
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2014R1A1A1005390 and NRF-2016R1E1A2020733).
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Kim, M., Kwon, T. & Kim, K. Can Human–Robot Interaction Promote the Same Depth of Social Information Processing as Human–Human Interaction?. Int J of Soc Robotics 10, 33–42 (2018). https://doi.org/10.1007/s12369-017-0428-5
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DOI: https://doi.org/10.1007/s12369-017-0428-5