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Realities vs expectations: children’s perception and imagination of AI

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Abstract

Based on Folk theory, Media Equation, and AI literacy research, the study constructed an interview outline and selected 72 students in 4th and 5th grade in three primary schools located in the Minhang and Putuo districts of Shanghai (two in the Minhang district and one in the Putuo district) as the study participants for focus group interviews. The study found that the availability of voice interaction is an essential basis for children to judge the level of intelligence of a machine; additionally, chatting is also the starting point for young children to build a close relationship with AI. Although AI cannot replace their friends, it can become a friend to them. While children expect the future of AI to be beyond the current level of intelligence and emotion and to enable the full use of machines in multiple scenarios and various fields, they are also concerned about issues such as privacy breaches that devices may cause in the future and believe that technology should not develop outside of human control.

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References

  • Apиcтapxoвa, И. Л. (1998). Turkle S. Life on the screen: Identity in the age of the Internet. New York: Simon & Schuster, 1995. Coциoлoгичecкий жypнaл, (3–4), C-304.

  • Bainbridge, W. A., Hart, J. W., Kim, E. S., & Scassellati, B. (2011). The benefits of interactions with physically present robots over video-displayed agents. International Journal of Social Robotics, 3(1), 41–52.

    Article  Google Scholar 

  • Barrat, J. (2015). Our final invention: artificial intelligence and the end of the human era.

  • Belpaeme, T., Baxter, P., Read, R., Wood, R., Cuayáhuitl, H., Kiefer, B., Racioppa, S., Kruijff-Korbayová, I., Athanasopoulos, G., Enescu, V., Looije, R., Neerincx, M., Demiris, Y., Ros-Espinoza, R., Beck, A., Cañamero, L., Hiolle, A., Lewis, M., Baroni, I., et al. (2012). Multimodal child-robot interaction: Building social bonds. Journal of Human-Robot Interaction, 1(2), 1–21.

    Google Scholar 

  • Beran, T. N., & Ramirez-Serrano, A. (2010). Can children have a relationship with a robot?. In International Conference on Human-Robot Personal Relationship (pp. 49–56). Springer.

  • Brockman, J. (Ed.). (2020). Possible minds: Twenty-five ways of looking at AI. Penguin.

    Google Scholar 

  • Brooks, H. (1991). Scientific literacy and the future labour force. Issues in Science Education. Science Competence in a Social and Ecological Context, 19–29.

  • Damon, W., Lerner, R. M., & Eisenberg, N. (Eds.). (2006). Handbook of child psychology, social, emotional, and personality development. John Wiley & Sons.

  • Druga, S., Williams, R., Breazeal, C., & Resnick, M. (2017). “Hey Google is it ok if I eat you?” Initial explorations in child-agent interaction. In Proceedings of the 2017 conference on interaction design and children (pp. 595–600).

  • Druga, S., Vu, S. T., Likhith, E., & Qiu, T. (2019). Inclusive AI literacy for kids around the world. In Proceedings of FabLearn 2019 (pp. 104–111).

  • Duck, S. E., Hay, D. F., Hobfoll, S. E., Ickes, W. E., & Montgomery, B. M. (1988). Handbook of personal relationships: Theory, research and interventions. John Wiley & Sons.

    Google Scholar 

  • Eslami, M., Karahalios, K., Sandvig, C., Vaccaro, K., Rickman, A., Hamilton, K., & Kirlik, A. (2016, May). First I “like” it, then I hide it: Folk Theories of Social Feeds. In Proceedings of the 2016 cHI conference on human factors in computing systems (pp. 2371–2382).

  • Fast, E., & Horvitz, E. (2017). Long-term trends in the public perception of artificial intelligence. In Proceedings of the AAAI conference on artificial intelligence (Vol. 31, No. 1).

  • Garvey, C. (1990). Play (Vol. 27). Harvard University Press.

    Google Scholar 

  • Gibson, M. A., & Ogbu, J. U. (1991). Minority status and schooling: A comparative study of immigrant and involuntary minorities. Garland Publishing, Inc., 717 Fifth Avenue, Suite 2500, New York, NY 10022; Okagaki, L. (2001). Triarchic model of minority children's school achievement. Educational Psychologist, 36(1), 9–20.

  • Glikson, E., & Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14(2), 627–660.

    Article  Google Scholar 

  • Han, X., Hu, F., Xiong, G., Liu, X., Gong, X., Niu, X., Shi, W., & Wang, X. (2018). Design of AI+ curriculum for primary and secondary schools in Qingdao. In 2018 Chinese Automation Congress (CAC) (pp. 4135–4140). IEEE.

  • Huang, X., & Zhang, F. (Eds.). (2022). Economic and Business Management. CRC Press. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1–16).

  • 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.

    Article  Google Scholar 

  • Kempton, W. (1986). Two theories of home heat control. Cognitive Science, 10(1), 75–90.

    MathSciNet  Google Scholar 

  • Kidd, C. D. (2003). Sociable robots: The role of presence and task in human-robot interaction (Doctoral dissertation, Massachusetts Institute of Technology).

  • Kong, S. C., Cheung, W. M. Y., & Zhang, G. (2021). Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds. Computers and Education: Artificial Intelligence, 2, 100026.

    Google Scholar 

  • Laver, J. (1975). Communicative functions of phatic communion. Organization of Behavior in Face-to-Face Interaction, 215, 238.

    Google Scholar 

  • Lee, I., Ali, S., Zhang, H., DiPaola, D., & Breazeal, C. (2021). Developing middle school students' AI literacy. In Proceedings of the 52nd ACM technical symposium on computer science education (pp. 191–197).

  • Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1–16).

  • Lovato, S., & Piper, A. M. (2015) “Siri, is this you?” Understanding young children's interactions with voice input systems. In Proceedings of the 14th international conference on interaction design and children (pp. 335–338).

  • Marcus, G., & Davis, E. (2019). Rebooting AI: Building artificial intelligence we can trust. Vintage.

    Google Scholar 

  • Mayer, R. E., Sobko, K., & Mautone, P. D. (2003). Social cues in multimedia learning: Role of speaker’s voice. Journal of Educational Psychology, 95(2), 419.

    Article  Google Scholar 

  • Mei, Q., Z, X. (2006) the Media Equation—from effect research to theoretical construction, Social Science Research.

  • Merton, R. K. (2008). Focused interview. Simon and Schuster.

    Google Scholar 

  • Miailhe, N., & Hodes, C. (2017). The third age of artificial intelligence. Field Actions Science Reports. The journal of field actions, (Special Issue 17), 6–11.

  • Nass, C. (2004). Etiquette equality: Exhibitions and expectations of computer politeness. Communications of the ACM, 47(4), 35–37.

    Article  Google Scholar 

  • Nass, C., & Steuer, J. (1993). Voices, boxes, and sources of messages: Computers and social actors. Human Communication Research, 19(4), 504–527.

    Article  Google Scholar 

  • Ng, D. T. K., Leung, J. K. L., Chu, K. W. S., & Qiao, M. S. (2021). AI literacy: Definition, teaching, evaluation and ethical issues. Proceedings of the Association for Information Science and Technology, 58(1), 504–509.

    Article  Google Scholar 

  • Norman, D. A. (1987). Human-computer interaction. Some observations on mental models. Morgan Kauf- mann Publishers Inc., 241–244.

  • Oh, K., & Kim, M. S. (2010). Social attributes of robotic products: Observations of child-robot interactions in a school environment. International Journal of Design, 4(1), 45–55.

    Google Scholar 

  • Rai, A., Constantinides, P., & Sarker, S. (2019). Next generation digital platforms: Toward human-AI hybrids. Mis Quarterly, 43(1), iii–ix.

    Google Scholar 

  • Reeves, B., & Nass, C. (1996). The media equation: How people treat computers, television, and new media like real people. Cambridge, UK, 10, 236605.

    Google Scholar 

  • Rip, A. (2019). Folk theories of nanotechnologists. Nanotechnology and Its Governance (pp. 56–74). Routledge.

    Chapter  Google Scholar 

  • Scaife, M., & van Duuren, M. (1995). Do computers have brains? What children believe about intelligent artifacts. British Journal of Developmental Psychology, 13(4), 367–377.

    Article  Google Scholar 

  • Schank, R. C. (1987). What is AI, anyway? AI Magazine, 8(4), 59–59.

    Google Scholar 

  • Serholt, S., & Barendregt, W. (2016, October). Robots tutoring children: Longitudinal evaluation of social engagement in child-robot interaction. In Proceedings of the 9th Nordic conference on human-computer interaction (pp. 1–10).

  • Shandwick, W. (2016). AI-ready or not: Artificial intelligence here we come!. What consumers think & What marketers need to know.

  • Stone, P., Brooks, R., Brynjolfsson, E., Calo, R., Etzioni, O., Hager, G., Hirschberg, J., Kalyanakrishnan, S., Kamar, E., Kraus, S., Leyton-Brown, K., Parkes, D., Press, W., Saxenian, A., Shah, J., Tambe, M., & Teller, A. (2022). Artificial intelligence and life in 2030: the one hundred year study on artificial intelligence. arXiv preprint arXiv:2211.06318.

  • Strommen, E., & Alexander, K. (1999, May). Emotional interfaces for interactive aardvarks: designing affect into social interfaces for children. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 528–535).

  • Su, J., Ng, D. T. K., & Chu, S. K. W. (2023). Artificial intelligence (AI) literacy in early childhood education: The challenges and opportunities. Computers and Education: Artificial Intelligence, 4, 100124.

    Google Scholar 

  • Sullivan, H. S. (2014). The interpersonal theory of psychiatry. An Introduction to Theories of Personality (pp. 137–156). Psychology Press.

    Google Scholar 

  • Sun, Y. (2016). Novice-Centric Visualizations for Machine Learning (Master's thesis, University of Waterloo).

  • Swidler, A. (1986). Culture in action: Symbols and strategies. American sociological review, 273–286.

  • Toff, B., & Nielsen, R. K. (2018). “I just google it”: Folk theories of distributed discovery. Journal of Communication, 68(3), 636–657.

    Article  Google Scholar 

  • Turkle, S. (1998). Cyborg Babies and Cy-dough-plasm. Cyborg babies: from techno-sex to techno-tots.

  • Van Dijck, J. (2013). The culture of connectivity: A critical history of social media. Oxford University Press.

    Book  Google Scholar 

  • Wellman, H. M., Cross, D., & Watson, J. (2001). Meta-analysis of theory-of-mind development: The truth about false belief. Child Development, 72(3), 655–684.

    Article  PubMed  CAS  Google Scholar 

  • Williams, R., Park, H. W., & Breazeal, C. (2019). A is for artificial intelligence: the impact of artificial intelligence activities on young children's perceptions of robots. In Proceedings of the 2019 CHI conference on human factors in computing systems (pp. 1–11).

  • Yonck, R. (2020). Heart of the machine: Our future in a world of artificial emotional intelligence. Arcade.

    Google Scholar 

  • Youniss, J., & Smollar, J. (1987). Adolescent relations with mothers, fathers and friends. University of Chicago Press.

    Google Scholar 

  • Zhang, F. (2014). An experimental study on the impact of different types of communication cues on impression formation in online interpersonal communication. Journalism and Communication Studies, 1, 109–125.

    CAS  Google Scholar 

  • Zimmerman, M. (2018). Teaching AI: exploring new frontiers for learning. International Society for Technology in Education.

    Google Scholar 

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  1. School of Communication, East China Normal University, Shanghai, China

    Lu Cai

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Cai, L. Realities vs expectations: children’s perception and imagination of AI. Int J Technol Des Educ (2024). https://doi.org/10.1007/s10798-024-09879-5

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