Can Human–Robot Interaction Promote the Same Depth of Social Information Processing as Human–Human Interaction?
- 682 Downloads
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.
KeywordsHumanoid robot Human–human interaction Human–robot interaction Social cognition Joint attention
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2014R1A1A1005390 and NRF-2016R1E1A2020733).
- 4.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 483–488Google Scholar
- 6.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):814–826CrossRefGoogle Scholar
- 9.Lewis M (2012) Social cognition and the acquisition of self. Springer, HeidelbergGoogle Scholar
- 13.Chaminade T, Okka MM (2013) Comparing the effect of humanoid and human face for the spatial orientation of attention. Front Neurorobot 7(12):1–7Google Scholar
- 19.Johansson M, Skantze G, Gustafson J (2013) Head pose patterns in multiparty human-robot team-building interactions. In: International conference on social robotics, pp 351–360Google Scholar
- 23.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):675–691Google Scholar
- 25.Baron-Cohen S (1997) Mindblindness: an essay on autism and theory of mind. MIT Press, CambridgeGoogle Scholar
- 29.Kim K, Mundy P (2012) Joint attention, social-cognition, and recognition memory in adults. Front Hum Neurosci 6(172):1–11Google Scholar
- 30.Ricks DJ, Colton MB (2010) Trends and considerations in robot-assisted autism therapy. In: 2010 IEEE international conference on robotics and automation (ICRA), pp 4354–4359Google Scholar
- 31.Scassellati B (2007) How social robots will help us to diagnose, treat, and understand autism. In: Robotics research, pp 552–563. Springer, BerlinGoogle Scholar
- 32.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):3726–34Google Scholar
- 34.Kaliouby RE (2005) Ming-reading machines: automated inference of complex mental States. University of CambridgeGoogle Scholar
- 38.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 1–8Google Scholar
- 39.Hall ET (1966) The hidden dimension. Doubleday, New YorkGoogle Scholar
- 42.Sheslow D, Adams W (2003) Wide range assessment of memory and learning-revised (WRAML-2). Administration and Technical Manual. Wide Range. Inc., WilmingtonGoogle Scholar
- 45.Vygotsky L (1978) Interaction between learning and development. Read Dev Child 23(3):34–41Google Scholar
- 53.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 2563–2568Google Scholar