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The Mind in the Machine: Mind Perception Modulates Gaze Aversion During Child–Robot Interaction


This study examined whether interacting with a humanoid robot influences children’s gaze aversion, an effortless strategy that people commonly use to facilitate thinking when asked challenging questions. Following the intentional stance model, we hypothesized that interacting with agents perceived as having a mind would modulate the social relevance assigned by the children to their interlocutor. Accordingly, we expected to observe an increase in children’s gaze aversion rates when questioned by an interaction partner believed to have a mind, compared to interaction conditions in which the questioner was believed to be a machine. To test this hypothesis, we involved 94 children in two experiments. In Experiment 1, the children interacted either with a humanoid robot (Human–Robot; n = 22) or with a human (Human–Human; n = 22) questioner. In Experiment 2, all the children interacted with a humanoid robot: one group was told the robot was controlled by a human (Avatar; n = 25), while the other group was told the robot was controlled by a computer algorithm (Machine; n = 25). Our results show that: (1) adopting an intentional stance (Human–Human; Avatar) increases gaze aversion rates; (2) gaze aversion increases and (3) response accuracy decreases as a function of question difficulty; (4) accuracy does not differ between interaction conditions. Based on these findings, we propose that gaze aversion rates might be considered an objective behavioural indicator of mind perception. Implications for robot-mediated education are also discussed.

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  1. 1.

    Cross ES, Hortensius R, Wykowska A (2019) From social brains to social robots: applying neurocognitive insights to human–robot interaction. Philos Trans R Soc B 374:20180024.

    Article  Google Scholar 

  2. 2.

    Wiese E, Metta G, Wykowska A (2017) Robots as intentional agents: using neuroscientific methods to make robots appear more social. Front Psychol 8:1663.

    Article  Google Scholar 

  3. 3.

    Kahn PH Jr, Gary HE, Shen S (2013) Children’s social relationships with current and near-future robots. Child Dev Perspect 7:32–37.

    Article  Google Scholar 

  4. 4.

    Serholt S, Barendregt W, Vasalou A, Alves-Oliveira P, Jones A, Petisca S, Paiva A (2017) The case of classroom robots: teachers’ deliberations on the ethical tensions. AI Soc 32:613–631.

    Article  Google Scholar 

  5. 5.

    Ehrlichman H, Micic D (2012) Why do people move their eyes when they think? Curr Dir Psychol Sci 21:96–100.

    Article  Google Scholar 

  6. 6.

    Glenberg AM, Schroeder JL, Robertson DA (1998) Averting the gaze disengages the environment and facilitates remembering. Mem Cogn 26:651–658.

    Article  Google Scholar 

  7. 7.

    Abeles D, Yuval-Greenberg S (2017) Just look away: gaze aversions as an overt attentional disengagement mechanism. Cognition 168:99–109.

    Article  Google Scholar 

  8. 8.

    Buchanan H, Markson L, Bertrand E, Greaves S, Parmar R, Paterson KB (2014) Effects of social gaze on visual-spatial imagination. Front Psychol 5:671.

    Article  Google Scholar 

  9. 9.

    Doherty-Sneddon G, Phelps FG (2005) Gaze aversion: a solution to cognitive or social difficulty? Mem Cogn 33:727–733.

    Article  Google Scholar 

  10. 10.

    Einstein GO, Earles JL, Collins HM (2002) Gaze aversion: spared inhibition for visual distraction in older adults. J Gerontol B Psychol Sci Soc Sci 57:P65–P73.

    Article  Google Scholar 

  11. 11.

    Markson L, Paterson KB (2009) Effects of gaze-aversion on visual-spatial imagination. Brit J Psychol 100:553–563.

    Article  Google Scholar 

  12. 12.

    Doherty-Sneddon G, Bonner L, Bruce V (2001) Cognitive demands of face monitoring: evidence for visuospatial overload. Mem Cogn 29:909–919.

    Article  Google Scholar 

  13. 13.

    Doherty-Sneddon G, Bruce V, Bonner L, Longbotham S, Doyle C (2002) Development of gaze aversion as disengagement from visual information. Dev Psychol 38:438–445.

    Article  Google Scholar 

  14. 14.

    Phelps FG, Doherty-Sneddon G, Warnock H (2006) Helping children think: gaze aversion and teaching. Brit J Dev Psychol 24:577–588.

    Article  Google Scholar 

  15. 15.

    Kleinke CL (1986) Gaze and eye contact: a research review. Psychol Bull 100:78–100

    Article  Google Scholar 

  16. 16.

    Kajimura S, Nomura M (2016) When we cannot speak: eye contact disrupts resources available to cognitive control processes during verb generation. Cognition 157:352–357.

    Article  Google Scholar 

  17. 17.

    Langton SR, Law AS, Burton AM, Schweinberger SR (2008) Attention capture by faces. Cognition 107:330–342.

    Article  Google Scholar 

  18. 18.

    Teufel C, Alexis DM, Clayton NS, Davis G (2010) Mental-state attribution drives rapid, reflexive gaze following. Atten Percept Psycho 72:695–705.

    Article  Google Scholar 

  19. 19.

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

    Article  Google Scholar 

  20. 20.

    Gray K, Young L, Waytz A (2012) Mind perception is the essence of morality. Psychol Inq 23:101–124.

    Article  Google Scholar 

  21. 21.

    Wiese E, Mandel A, Shaw T, Smith M (2019) Implicit mind perception alters vigilance performance because of cognitive conflict processing. J Exp Psychol Appl 25:25–40.

    Article  Google Scholar 

  22. 22.

    Epley N, Waytz A (2010) Mind perception. In: Fiske ST, Gilbert DT, Lindzey G (eds) Handbook of social psychology. Wiley, Hoboken.

    Chapter  Google Scholar 

  23. 23.

    Waytz A, Gray K, Epley N, Wegner DM (2010) Causes and consequences of mind perception. Trends Cogn Sci 14:383–388.

    Article  Google Scholar 

  24. 24.

    Capozzi F, Ristic J (2018) How attention gates social interactions. Ann NY Acad Sci 1426:179–198.

    Article  Google Scholar 

  25. 25.

    Dennett DC (1971) Intentional systems. J Philos 68:87–106.

    Article  Google Scholar 

  26. 26.

    Dennett DC (1987) The intentional stance. MIT Press, Cambridge

    Google Scholar 

  27. 27.

    Hortensius R, Cross ES (2018) From automata to animate beings: the scope and limits of attributing socialness to artificial agents. Ann NY Acad Sci 1426:93–110.

    Article  Google Scholar 

  28. 28.

    Caruana N, de Lissa P, McArthur G (2017) Beliefs about human agency influence the neural processing of gaze during joint attention. Soc Neurosci 12:194–206.

    Article  Google Scholar 

  29. 29.

    Wiese E, Buzzell GA, Abubshait A, Beatty PJ (2018) Seeing minds in others: mind perception modulates low-level social-cognitive performance and relates to ventromedial prefrontal structures. Cogn Affect Behav Neurosci 18:837–856.

    Article  Google Scholar 

  30. 30.

    Wykowska A, Chaminade T, Cheng G (2016) Embodied artificial agents for understanding human social cognition. Philos Trans R Soc B 371:20150375.

    Article  Google Scholar 

  31. 31.

    Wiese E, Wykowska A, Zwickel J, Müller HJ (2012) I see what you mean: how attentional selection is shaped by ascribing intentions to others. PLoS ONE 7:e45391.

    Article  Google Scholar 

  32. 32.

    Wiese E, Wykowska A, Müller HJ (2014) What we observe is biased by what other people tell us: beliefs about the reliability of gaze behavior modulate attentional orienting to gaze cues. PLoS ONE 9:e94529.

    Article  Google Scholar 

  33. 33.

    Wykowska A, Wiese E, Prosser A, Müller HJ (2014) Beliefs about the minds of others influence how we process sensory information. PLoS ONE 9:e94339.

    Article  Google Scholar 

  34. 34.

    Kiesler S, Powers A, Fussell SR, Torrey C (2008) Anthropomorphic interactions with a robot and robot-like agent. Soc Cogn 26:169–181.

    Article  Google Scholar 

  35. 35.

    Pfeiffer UJ, Timmermans B, Bente G, Vogeley K, Schilbach L (2011) A non-verbal Turing test: differentiating mind from machine in gaze-based social interaction. PLoS ONE 6:e27591.

    Article  Google Scholar 

  36. 36.

    Abubshait A, Wiese E (2017) You look human, but act like a machine: agent appearance and behavior modulate different aspects of human–robot interaction. Front Psychol 8:1393.

    Article  Google Scholar 

  37. 37.

    Özdem C, Wiese E, Wykowska A, Müller H, Brass M, Van Overwalle F (2017) Believing androids—fMRI activation in the right temporo-parietal junction is modulated by ascribing intentions to non-human agents. Soc Neurosci 12:582–593.

    Article  Google Scholar 

  38. 38.

    Schellen E, Wykowska A (2019) Intentional mindset toward robots—open questions and methodological challenges. Front Robot AI 11:139.

    Article  Google Scholar 

  39. 39.

    Haley KJ, Fessler DM (2005) Nobody’s watching?: Subtle cues affect generosity in an anonymous economic game. Evol Hum Behav 26:245–256.

    Article  Google Scholar 

  40. 40.

    Doherty-Sneddon G, McAuley S (2000) Influence of video-mediation on adult–child interviews: implications for the use of the live link with child witnesses. Appl Cogn Psychol 14:379–392.;2-T

    Article  Google Scholar 

  41. 41.

    Lapidot-Lefler N, Barak A (2012) Effects of anonymity, invisibility, and lack of eye contact on toxic online disinhibition. Comput Hum Behav 28:434–443.

    Article  Google Scholar 

  42. 42.

    Riby DM, Whittle L, Doherty-Sneddon G (2012) Physiological reactivity to faces via live and video-mediated communication in typical and atypical development. J Clin Exp Neuropsychol 34:385–395.

    Article  Google Scholar 

  43. 43.

    Kruger J, Epley N, Parker J, Ng ZW (2005) Egocentrism over e-mail: can we communicate as well as we think? J Pers Soc Psychol 89:925–936.

    Article  Google Scholar 

  44. 44.

    Grossmann T (2017) The eyes as windows into other minds: an integrative perspective. Perspect Psychol Sci 12:107–121.

    Article  Google Scholar 

  45. 45.

    Heberlein AS, Adolphs R (2004) Impaired spontaneous anthropomorphizing despite intact perception and social knowledge. PNAS 101:7487–7491.

    Article  Google Scholar 

  46. 46.

    Amodio DM, Frith CD (2006) Meeting of minds: the medial frontal cortex and social cognition. Nat Rev Neurosci 7:268.

    Article  Google Scholar 

  47. 47.

    Kampe KK, Frith CD, Frith U (2003) “Hey John”: signals conveying communicative intention toward the self activate brain regions associated with “mentalizing”, regardless of modality. J Neurosci 23:5258–5263.

    Article  Google Scholar 

  48. 48.

    Pelphrey KA, Morris JP (2006) Brain mechanisms for interpreting the actions of others from biological-motion cues. Curr Dir Psychol Sci 15:136–140.

    Article  Google Scholar 

  49. 49.

    Colombatto C, van Buren B, Scholl BJ (2019) Intentionally distracting: working memory is disrupted by the perception of other agents attending to you—even without eye-gaze cues. Psychon B Rev 26:951–957.

    Article  Google Scholar 

  50. 50.

    Conty L, Gimmig D, Belletier C, George N, Huguet P (2010) The cost of being watched: stroop interference increases under concomitant eye contact. Cognition 115:133–139.

    Article  Google Scholar 

  51. 51.

    Foulsham T, Cheng JT, Tracy JL, Henrich J, Kingstone A (2010) Gaze allocation in a dynamic situation: effects of social status and speaking. Cognition 117:319–331.

    Article  Google Scholar 

  52. 52.

    Land MF, Hayhoe M (2001) In what ways do eye movements contribute to everyday activities? Vis Res 41:3559–3565.

    Article  Google Scholar 

  53. 53.

    Senju A, Johnson MH (2009) The eye contact effect: mechanisms and development. Trends Cogn Sci 13:127–134.

    Article  Google Scholar 

  54. 54.

    Desideri L, Ottaviani C, Malavasi M, di Marzio R, Bonifacci P (2019) Emotional processes in human–robot interaction during brief cognitive testing. Comput Hum Behav 90:331–342.

    Article  Google Scholar 

  55. 55.

    Brink KA, Gray K, Wellman HM (2017) Creepiness creeps in: uncanny valley feelings are acquired in childhood. Child Dev 90:1202–1214.

    Article  Google Scholar 

  56. 56.

    Severson RL, Lemm KM (2016) Kids see human too: adapting an individual differences measure of anthropomorphism for a child sample. J Cogn Dev 17:122–141.

    Article  Google Scholar 

  57. 57.

    Beattie GW (1981) A further investigation of the cognitive interference hypothesis of gaze patterns during conversation. Brit J Soc Psychol 20:243–248.

    Article  Google Scholar 

  58. 58.

    Fabes RA, Eisenberg N, Eisenbud L (1993) Behavioral and physiological correlates of children’s reactions to others in distress. Dev Psychol 29:655–663.

    Article  Google Scholar 

  59. 59.

    Colonnello V, Petrocchi N, Farinelli M, Ottaviani C (2017) Positive social interactions in a lifespan perspective with a focus on opioidergic and oxytocinergic systems: implications for neuroprotection. Curr Neuropharmacol 15:543–561.

    Article  Google Scholar 

  60. 60.

    Porges SW (2003) Social engagement and attachment. Ann NY Acad Sci 1008:31–47.

    Article  Google Scholar 

  61. 61.

    Porges SW (2007) The polyvagal perspective. Biol Psychol 74:116–143.

    Article  Google Scholar 

  62. 62.

    Bunford N, Evans SW, Zoccola PM, Owen JS, Flory K, Spiel CF (2017) Correspondence between heart rate variability and emotion dysregulation in children, including children with ADHD. J Abnorm Psychol 45:1325–1337.

    Article  Google Scholar 

  63. 63.

    Hietanen JK (2018) Affective eye contact: an integrative review. Front Psychol 9:1587.

    Article  Google Scholar 

  64. 64.

    Thalheimer W, Cook S (2002). How to calculate effect sizes from published research articles: a simplified methodology. Accessed 11 Dec 2018

  65. 65.

    Faul F, Erdfelder E, Lang A-G, Buchner A (2007) G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 39:175–191.

    Article  Google Scholar 

  66. 66.

    Orsini A, Pezzuti L, Picone L (2011) WISC-IV. Contributo alla taratura Italiana. [WISC-IV Italian Edition]. Giunti, OS, Firenze

    Google Scholar 

  67. 67.

    Biancardi A, Bachmann C, Nicoletti C (2016) Batteria discalculia evolutiva. Erikson, Trento ISBN: 9788859007784

    Google Scholar 

  68. 68.

    Softbank robotics documentation. Accessed Mar 2020

  69. 69.

    Caruana N, McArthur G (2019) The mind minds minds: the effect of intentional stance on the neural encoding of joint attention. Cogn Affect Behav Neurosci.

    Article  Google Scholar 

  70. 70.

    Cianchetti C, Sannio Fascello G (2001) Scale psichiatriche di autosomministrazione per fanciulli e adolescenti [Self administrated psychiatric scales for children and adolescents] (SAFA). Giunti-OS, Firenze

    Google Scholar 

  71. 71.

    Baiocco R, Manzi D, Lonigro A, Petrocchi N, Laghi F, Ioverno S, Ottaviani C (2017) A kid-friendly tool to assess rumination in children and early adolescents: relationships with mother psychopathology and family functioning. J Child Fam Stud 26:2703–2715.

    Article  Google Scholar 

  72. 72.

    Bonifacci P, Nori R (2016) KBIT-2. Kaufman brief intelligence test second edition. Contributo alla taratura italiana [Contribution to Italian standardization]. Giunti-OS, Firenze

    Google Scholar 

  73. 73.

    Niskanen JP, Tarvainen MP, Ranta-Aho PO, Karjalainen PA (2004) Software for advanced HRV analysis. Comput Methods Programs Biomed 76:73–81.

    Article  Google Scholar 

  74. 74.

    Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology (1996) Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Circulation 93:1043–1065.

    Article  Google Scholar 

  75. 75.

    Penttila J, Helminen A, Jartti T, Kuusela T, Huikuri HV, Tulppo MP, Coffeng R, Scheinin H (2001) Time domain, geometrical and frequency domain analysis of cardiac vagal outflow: effects of various respiratory patterns. Clin Physiol Funct Imaging 21:365–376.

    Article  Google Scholar 

  76. 76.

    Jennings JR, Kamarck T, Stewart C, Eddy M, Johnson P (1992) Alternate cardiovascular baseline assessment techniques: vanilla or resting baseline. Psychophysiology 29:742–750.

    Article  Google Scholar 

  77. 77.

    Norman GR, Streiner DL (2008) Biostatistics: the bare essentials. PMPH USA, Raleigh

    Google Scholar 

  78. 78.

    JASP Team (2019) JASP (Version 0.11.1) [Computer software]. Accessed 15 Oct 2019

  79. 79.

    Postma M, Goedhart J (2019) PlotsOfData—a web app for visualizing data together with their summaries. PLoS Biol 17:e3000202.

    Article  Google Scholar 

  80. 80.

    Bonifacci P, Ricciardelli P, Lugli L, Pellicano A (2008) Emotional attention: effects of emotion and gaze direction on overt orienting of visual attention. Cogn Process 9:127–135.

    Article  Google Scholar 

  81. 81.

    Caponi B, Cornoldi C, Falco G, Focchiatti R, Lucangeli D (2012) Test MEMA. Test di valutazione di atteggiamento, credenze e sistema di controllo. Erickson, Trento

    Google Scholar 

  82. 82.

    Marzocchi GM, Re A, Cornoldi C (2010) BIA—batteria italiana per l’ADHD per la valutazione dei bambini con deficit di attenzione/iperattività. Erickson, Trento

    Google Scholar 

  83. 83.

    Costa M, Dinsbach W, Manstead AS, Bitti PER (2001) Social presence, embarrassment, and nonverbal behavior. J Nonverbal Behav 25:225–240.

    Article  Google Scholar 

  84. 84.

    Mosconi MW, Mack PB, McCarthy G, Pelphrey KA (2005) Taking an “intentional stance” on eye-gaze shifts: a functional neuroimaging study of social perception in children. Neuroimage 27:247–252.

    Article  Google Scholar 

  85. 85.

    Caruana N, Spirou D, Brock J (2017) Human agency beliefs influence behaviour during virtual social interactions. PeerJ 5:e3819.

    Article  Google Scholar 

  86. 86.

    Saygin AP, Chaminade T, Ishiguro H, Driver J, Frith C (2012) The thing that should not be: predictive coding and the uncanny valley in perceiving human and humanoid robot actions. Soc Cogn Affect Neurosci 7:413–422.

    Article  Google Scholar 

  87. 87.

    Mwangi E, Barakova EI, Díaz M, Mallofré AC, Rauterberg M (2018) Dyadic gaze patterns during child–robot collaborative gameplay in a tutoring interaction. In: 2018 27th IEEE international symposium on robot and human interactive communication (RO-MAN), pp 856–861.

  88. 88.

    Broadbent E, Feerst DA, Lee SH, Robinson H, Albo-Canals J, Ahn HS, MacDonald BA (2018) How could companion robots be useful in rural schools? Int J Soc Robot 10:295–307.

    Article  Google Scholar 

  89. 89.

    Belpaeme T, Kennedy J, Ramachandran A, Scassellati B, Tanaka F (2018) Social robots for education: a review. Sci Robot 3:eaat5954.

    Article  Google Scholar 

  90. 90.

    Sage KD, Baldwin D (2010) Social gating and pedagogy: mechanisms for learning and implications for robotics. Neural Netw 23:1091–1098.

    Article  Google Scholar 

  91. 91.

    Chernyak N, Gary HE (2016) Children’s cognitive and behavioral reactions to an autonomous versus controlled social robot dog. Early Educ Dev 27:1175–1189.

    Article  Google Scholar 

  92. 92.

    Chun MM, Golomb JD, Turk-Browne NB (2011) A taxonomy of external and internal attention. Annu Rev Psychol 62:73–101.

    Article  Google Scholar 

  93. 93.

    Desideri L, Negrini M, Malavasi M, Tanzini D, Rouame A, Cutrone MC et al (2018) Using a humanoid robot as a complement to interventions for children with autism spectrum disorder: a pilot study. Adv Neurodev Disord 2:273–285.

    Article  Google Scholar 

  94. 94.

    Desideri L, Ottaviani C, Cecchetto C, Bonifacci P (2019) Mind wandering, together with test anxiety and self-efficacy, predicts student’s academic self-concept but not reading comprehension skills. Brit J Educ Psychol 89:307–323.

    Article  Google Scholar 

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Desideri, L., Bonifacci, P., Croati, G. et al. The Mind in the Machine: Mind Perception Modulates Gaze Aversion During Child–Robot Interaction. Int J of Soc Robotics 13, 599–614 (2021).

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  • Child–robot interaction
  • Gaze aversion
  • Social processes
  • Mind perception
  • Intentional stance model