Desarrollo de la empatía a través de la Inteligencia Artificial Socioemocional

  1. María Isabel Gómez-León 1
  1. 1 Universidad Internacional de La Rioja
    info

    Universidad Internacional de La Rioja

    Logroño, España

    ROR https://ror.org/029gnnp81

Revista:
Papeles del psicólogo

ISSN: 0214-7823,  1886-1415

Ano de publicación: 2022

Título do exemplar: Conducta suicida en adolescentes. La disforia de género a debate

Volume: 43

Número: 3

Páxinas: 218-224

Tipo: Artigo

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Outras publicacións en: Papeles del psicólogo

Resumo

It is expected that in the near future robots will be increasingly involved in social roles, however, understanding how students learn empathic skills, and how technology can support this process, is an important but under-researched area in artificial intelligence. This paper analyzes the factors that contribute to the development of empathy from early childhood and the variables of robotic empathy that could help promote this learning. It has been found that social emotional artificial intelligence (SEAI) has already successfully implemented some of the human mechanisms of empathy that are present during the first years of life. The current state of SEAI research is far from achieving full empathic capacity, but it can provide useful tools to promote empathic skills, the basis of social cooperation and ethical and prosocial behavior, from childhood.

Referencias bibliográficas

  • Ali, S., Park, H., & Breazeal, C. (2021). A social robot’s influence on children’s figural creativity during gameplay. International Journal of Child-Computer Interaction, 28, 100234. https://doi.org/10.1016/j.ijcci.2020.100234
  • Banisetty, S. B., Rajamohan, V., Vega, F., & Feil-Seifer, D. (2021). A deep learning approach to Multi-Context Socially-Aware Navigation. 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), 2021, pp. 23-30. https://doi.org/10.1109/RO-MAN50785.2021.9515424.
  • Bartneck, C., & Forlizzi, J. (2004). A design-centred framework for social human-robot interaction. In RO-MAN 2004 : 13th IEEE International Workshop on Robot and Human Interactive Communication, September 20-22, 2004, Kurashiki (pp. 591-594). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ROMAN.2004.1374827
  • Bisquerra, R., & Alzina, S. (2017). Psicología positiva, educación emocional y el Programa Aulas Felices. Papeles del Psicólogo, 38(1), 58-65. https://doi.org/10.23923/pap.psicol2017.2822
  • Buyukgoz, S., Pandey, A. K., Chamoux, M., & Chetouani, M. (2021). Exploring behavioral creativity of a proactive robot. Frontiers in Robotics and AI, 8, 694177. https://doi.org/10.3389/frobt.2021.694177
  • Castellano, G., Leite, I., & Paiva, A. (2017). Detecting perceived quality of interaction with a robot using contextual features. Autonomous Robots, 41, 1245–1261. https://doi.org/10.1007/s10514-016-9592-y
  • Causo, A., Vo, G. T., Chen, I., & Yeo, S. H. (2016). Design of robots used as education companion and tutor. In Robotics and mechatronics (pp. 75- 84). Springer, Cham. https://doi.org/10.1007/978-3-319-22368-1_8
  • de Waal, F. B. (2012). The antiquity of empathy. Science (New York, N.Y.), 336(6083), 874-876. https://doi.org/10.1126/science.1220999
  • de Waal, F., & Preston, S. D. (2017). Mammalian empathy: Behavioural manifestations and neural basis. Nature Reviews Neuroscience, 18(8), 498–509. https://doi.org/10.1038/nrn.2017.72
  • Feng, S., Wang, X., Wang, Q., Fang, J., Wu, Y., Yi, L., & Wei, K. (2018). The uncanny valley effect in typically developing children and its absence in children with autism spectrum disorders. PloS one, 13(11), e0206343. https://doi.org/10.1371/journal.pone.0206343
  • Geangu, E., Benga, O., Stahl, D., & Striano, T. (2010). Contagious crying beyond the first days of life. Infant Behavior & Development, 33(3), 279–288. https://doi.org/10.1016/j.infbeh.2010.03.004
  • Gómez-León, M. I. (2020). Desarrollo de la alta capacidad durante la infancia temprana. Papeles del Psicólogo, 41(2),147-158. https://doi.org/10.23923/pap.psicol2020.2930
  • Goris, K., Saldien, J., Vanderborght, B., & Lefeber, D. (2011). Mechanical Design of the huggable Robot Probo. International Journal Humanoid Robotics, 8, 481-511. https://doi.org/10.1142/S0219843611002563
  • Grosse Wiesmann, C., Friederici, A. D., Singer, T., & Steinbeis, N. (2020). Two systems for thinking about others’ thoughts in the developing brain. Proceedings of the National Academy of Sciences of the United States of America, 117(12), 6928–6935. https://doi.org/10.1073/pnas.1916725117
  • Ishihara, H., Wu, B., & Asada, M. (2018). Identification and evaluation of the face system of a child android robot Affetto for surface motion design. Frontiers in Robotics and AI, 5, 119. https://doi.org/10.3389/frobt.2018.00119
  • Kahn, P. H., Jr, Kanda, T., Ishiguro, H., Freier, N. G., Severson, R. L., Gill, B. T., Ruckert, J. H., & Shen, S. (2012). “Robovie, you’ll have to go into the closet now”: Children’s social and moral relationships with a humanoid robot. Developmental Psychology, 48(2), 303–314. https://doi.org/10.1037/a0027033
  • Kanda, T., Sato, R., Saiwaki, N., & Ishiguro, H. (2007). A two-month field trial in an elementary school for long-term human-robot interaction. IEEE Transactions on Robotics, 23(5), 962–971. https://doi.org/10.1109/TRO.2007.904904
  • Kozima, H., Michalowski, M. P., & Nakagawa, C. (2009). Keepon. International Journal of social robotics, 1(1), 3-18. https://doi.org/10.1007/s12369-008-0009-8
  • Lewkowicz, D. J., & Ghazanfar, A. A. (2012). The development of the uncanny valley in infants. Developmental Psychobiology, 54(2), 124–132. https://doi.org/10.1002/dev.20583
  • Manzi, F., Peretti, G., Di Dio, C., Cangelosi, A., Itakura, S., Kanda, T.,Ishiguro, H., Massaro, D., & Marchetti, A. (2020). A robot is not worth another: Exploring children’s mental state attribution to different humanoid robots. Frontiers in Psychology, 11, 2011. https://doi.org/10.3389/fpsyg.2020.02011
  • McStay, A., & Rosner, G. (2021). Emotional artificial intelligence in children’s toys and devices: Ethics, governance and practical remedies. Big Data & Society. https://doi.org/10.1177/2053951721994877
  • Mori, M., MacDorman, K. F., & Kageki, N. (2012). The uncanny valley. IEEE Robotics and Automation Magazine, 19(2), 98–100. https://doi.org/10.1109/MRA.2012.2192811
  • Nitsch, V., & Popp, M. (2014). Emotions in robot psychology. Biological Cybernetics, 108(5), 621–629. https://doi.org/10.1007/S00422-014-0594-6
  • Pandey, A. K., Ali, M., & Alami, R. (2013). Towards a task-aware proactive sociable robot based on multi-state perspective-taking. International Journal of Social Robotics, 5, 215-236. https://doi.org/10.1007/s12369-013-0181-3
  • Park, S., & Whang, M. (2022). Empathy in human–robot interaction: Designing for social robots. International Journal of Environmental Research and Public Health, 19, 1889. https://doi.org/10.3390/ijerph19031889
  • Park, S., Kim, S. P., & Whang, M. (2021). Individual’s social perception of virtual avatars embodied with their habitual facial expressions and facial appearance. Sensors (Basel, Switzerland), 21(17), 5986. https://doi.org/10.3390/s21175986
  • Schiff, D. (2021). Out of the laboratory and into the classroom: the future of artificial intelligence in education. AI & society, 36(1), 331-348. https://doi.org/10.1007/s00146-020-01033-8
  • Serholt, S., Pareto, L., Ekström, S., & Ljungblad, S. (2020). Trouble and repair in child-robot interaction: A study of complex interactions with a robot Tutee in a primary school Classroom. Frontiers in Robotics and AI, 7, 46. https://doi.org/10.3389/frobt.2020.00046
  • Stevens, F., & Taber, K. (2021). The neuroscience of empathy and compassion in pro-social behavior. Neuropsychologia, 159, 107925. https://doi.org/10.1016/j.neuropsychologia.2021.107925
  • Tanaka, F., Cicourel, A., & Movellan, J. R. (2007). Socialization between toddlers and robots at an early childhood education center. Proceedings of the National Academy of Sciences of the United States of America, 104(46), 17954–17958. https://doi.org/10.1073/pnas.0707769104
  • Tejwani, R., Kuo, Y., Shu, T., Katz, B., & Barbu, A. (2022). Social interactions as recursive MDPs. Proceedings of the 5th Conference on Robot Learning, in Proceedings of Machine Learning Research, 164, 949-958. https://proceedings.mlr.press/v164/tejwani22a.html.
  • Vircikova, M., Magyar, G., & Sincak, P. (2015). The affective loop: A tool for autonomous and adaptive emotional human-robot interaction. In Robot Intelligence Technology and Applications 3 (pp. 247-254). Springer, Cham. https://doi.org/10.1007/978-3-319-16841-8_23
  • Watanabe, A., Ogino, M., Asada, M. (2007). Mapping facial expression to internal states based on intuitive parenting. Journal of Robotics and Mechatronics, 19(3), 315–323. http://www.er.ams.eng.osaka-u.ac.jp/Paper/2007/Watanabe07b.pdf
  • Woo, H., LeTendre, G. K., Pham-Shouse, T., & Xiong, Y. (2021). The use of social robots in classrooms: A review of field-based studies. Educational Research Review, 33, 100388. https://doi.org/10.1016/j.edurev.2021.100388
  • Wood, L. J., Dautenhahn, K., Rainer, A., Robins, B., Lehmann, H., & Syrdal, D. S. (2013). Robot-mediated interviews-how effective is a humanoid robot as a tool for interviewing young children?. PloS one, 8(3), e59448. https://doi.org/10.1371/journal.pone.0059448
  • Yohanan, S., MacLean, K. E. (2012). The role of affective touch in humanrobot interaction: Human intent and expectations in touching the haptic creature. International Journal of Social Robotics, 4, 163–180. https://doi.org/10.1007/s12369-011-0126-7
Fonte de datos: Dialnet