Talking with machines: Can conversational technologies serve as children's social partners?
Open accessAbstract
Back-and-forth conversations with others are vital for children's development in the early years. While children's conversation partners have traditionally been their parents, teachers, and peers, recent advances in artificial intelligence have led to the introduction of machines that understand human speech and generate natural responses, and thus can engage children in conversations. As these technologies become increasingly ubiquitous in children's lives, questions arise as to how they might affect children's development: How do children interact with, perceive, and learn from conversational technologies? Can these technologies serve as children's social partners? In this article, I detail what we know about these topics and discuss the possible implications of conversational technologies for children's shifting media landscape. I also suggest research agendas that can unpack the complex interplay among children, their social contexts, and conversational technology.
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Xu [58] suggests that children engage in more complex conversations with humans, particularly because humans can use nonverbal cues such as nodding and eye contact, which AI currently lacks.
“Similarly, Xu [58], in her article in Child Development Perspectives, suggests that children engage in more complex conversations with humans, particularly because humans can use nonverbal cues (e.g., nodding, eye contact), which AI currently lacks.”
From Child-AI Co-Creation: A Review of the Current Research Landscape and a Proposal for Six Design Considerations (2025) · cites this paper as [58]
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Cites
Child's Conception of the World
Piaget, J. (2013) · Routledge eBooks · doi:10.4324/9781315006215 · Cited by 2,702 · see citing works
Gelman, R. (1990) · Cognitive Science · doi:10.1207/s15516709cog1401_5 · Cited by 498 · see citing works
Language Matters: Denying the Existence of the 30-Million-Word Gap Has Serious Consequences
Golinkoff, R. M., Hoff, E., Rowe, M. L., Tamis‐LeMonda, C. S., & Hirsh‐Pasek, K. (2018) · Child Development · doi:10.1111/cdev.13128 · Cited by 476 · see citing works
Communication Breakdowns Between Families and Alexa
Beneteau, E., Richards, O. K., Zhang, M., Kientz, J. A., Yip, J., & Hiniker, A. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300473 · Cited by 313 · see citing works
Voices, Boxes, and Sources of Messages.
Nass, C., & Steuer, J. (1993) · Human Communication Research · doi:10.1111/j.1468-2958.1993.tb00311.x · Cited by 278 · see citing works
Screen media and language development in infants and toddlers: An ecological perspective
Linebarger, D. L., & Vaala, S. E. (2010) · Developmental Review · doi:10.1016/j.dr.2010.03.006 · Cited by 219 · see citing works
Melson, G. F., Kahn, P. H., Beck, A. M., & Friedman, B. (2009) · Journal of Social Issues · doi:10.1111/j.1540-4560.2009.01613.x · Cited by 195 · see citing works
Xu, Y., Wang, D., Collins, P., Lee, H., & Warschauer, M. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.104059 · Cited by 180 · see citing works
Self-citationZhang, Z., Xu, Y., Wang, Y., Yao, B., Ritchie, D., Wu, T., Yu, M., Wang, D., & Li, T. J.-J. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517479 · Cited by 174 · see citing works
Self-citationYoung Children Treat Robots as Informants
Breazeal, C., Harris, P. L., DeSteno, D. A., Kory-Westlund, J. M., Dickens, L. R., & Jeong, S. (2016) · Topics in Cognitive Science · doi:10.1111/tops.12192 · Cited by 164 · see citing works
Media as Social Partners: The Social Nature of Young Children’s Learning From Screen Media
Richert, R. A., Robb, M. B., & Smith, E. I. (2011) · Child Development · doi:10.1111/j.1467-8624.2010.01542.x · Cited by 155 · see citing works
Growing up in the digital age: Early learning and family media ecology
Barr, R. (2019) · Current Directions in Psychological Science · doi:10.1177/0963721419838245 · Cited by 147 · see citing works
Hey Google, Do Unicorns Exist?
Lovato, S. B., Piper, A. M., & Wartella, E. A. (2019) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/3311927.3323150 · Cited by 137 · see citing works
When and How Do Interactive Digital Media Help Children Connect What They See On and Off the Screen?
Kirkorian, H. L. (2018) · Child Development Perspectives · doi:10.1111/cdep.12290 · Cited by 135 · see citing works
Liao, Q. V., Mas-ud Hussain, M., Chandar, P., Davis, M., Khazaeni, Y., Crasso, M. P., Wang, D., Muller, M., Shami, N. S., & Geyer, W. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173577 · Cited by 116 · see citing works
Xu, Y., Aubele, J., Vigil, V., Bustamante, A. S., Kim, Y.-S., & Warschauer, M. (2022) · Child Development · doi:10.1111/cdev.13708 · Cited by 113 · see citing works
Self-citationMedia and the well-being of children and adolescents
Jordan, A. B., & Römer, D. (2014) · Cited by 111 · see citing works
Druga, S., Williams, R., Park, H. W., & Breazeal, C. (2018) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/3202185.3202741 · Cited by 93 · see citing works
What Are You Talking To?: Understanding Children's Perceptions of Conversational Agents
Xu, Y., & Warschauer, M. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376416 · Cited by 82 · see citing works
Self-citationExploring young children's engagement in joint reading with a conversational agent
Xu, Y., & Warschauer, M. (2020) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/3392063.3394417 · Cited by 79 · see citing works
Self-citationCommunicative and social consequences of interactions with voice assistants
Aeschlimann, S., Bleiker, M., Wechner, M., & Gampe, A. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106466 · Cited by 75 · see citing works
Richards, M. N., & Calvert, S. L. (2016) · Springer eBooks · doi:10.1007/978-3-319-45102-2_9 · Cited by 74 · see citing works
Children’s future parasocial relationships with media characters: the age of intelligent characters
Brunick, K. L., Putnam, M. M., McGarry, L. E., Richards, M. N., & Calvert, S. L. (2016) · Journal of Children and Media · doi:10.1080/17482798.2015.1127839 · Cited by 71 · see citing works
Garg, R., & Sengupta, S. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376631 · Cited by 68 · see citing works
Hoffman, A., Owen, D., & Calvert, S. (2021) · Human Behavior and Emerging Technologies · doi:10.1002/hbe2.271 · Cited by 55 · see citing works
Children’s trust in and learning from voice assistants.
Girouard‐Hallam, L. N., & Danovitch, J. H. (2022) · Developmental Psychology · doi:10.1037/dev0001318 · Cited by 55 · see citing works
Young Children’s Mathematical Learning From Intelligent Characters
Calvert, S. L., Putnam, M. M., Aguiar, N. R., Ryan, R. M., Wright, C. A., Liu, Y. H. A., & Barba, E. (2019) · Child Development · doi:10.1111/cdev.13341 · Cited by 48 · see citing works
Peebles, A. L., Bonus, J. A., & Mares, M. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.03.039 · Cited by 34 · see citing works
Xu, Y., Vigil, V., Bustamante, A. S., & Warschauer, M. (2022) · Journal of Applied Developmental Psychology · doi:10.1016/j.appdev.2022.101439 · Cited by 28 · see citing works
Self-citationArgumentative Discourse of Kindergarten Children: Features of Peer Talk and Children-Teacher Talk
Ehrlich, S. Z. (2011) · Journal of Research in Childhood Education · doi:10.1080/02568543.2011.580040 · Cited by 23 · see citing works
Can Conversational Agents Change the Way Children Talk to People?
Hiniker, A., Wang, A., Tran, J., Zhang, M. R., Radesky, J. S., Sobel, K., & Hong, S.-S. (2021) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/3459990.3460695 · Cited by 19 · see citing works
Intelligent digital beings as children’s imaginary social companions
Calvert, S. L. (2021) · Journal of Children and Media · doi:10.1080/17482798.2021.1896200 · Cited by 16 · see citing works
Why doesn't the conversational agent understand me?
Monarca, I., Cibrian, F. L., Mendoza, A., et al. (2020) · Adjunct ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers (UbiComp/ISWC) · doi:10.1145/3410530.3414401 · Cited by 12 · see citing works
Conversation as a system of social interaction
Myllyniemi, R. (1986) · Language & Communication · doi:10.1016/0271-5309(86)90019-4 · Cited by 11 · see citing works
Xu, Y. (2023) · doi:10.35542/osf.io/m3ej9 · Cited by 3 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- Reeves, B., & Nass, C. (1996). The media equation: How people treat computers, television, and new media like real people. Cambridge University Press.
Cited by
Sorted by citations
Cai, Z., Han, A., Zhou, X., Gazulla, E. D., & Peppler, K. (2025) · Proceedings of the 24th Interaction Design and Children · doi:10.1145/3713043.3731506 · Cited by 17 · see citing works
- Authors
- Xu, Y.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Xu, Ying
- ORCID
- Xu, Ying
- Venue
- Child Development Perspectives
- Publisher
- Oxford University Press (OUP)
- Published
- 2023-02-01
- Volume
- 17
- Issue
- 1
- Pages
- 53-58
- ISSN
- 1750-8592 (ISSN-L)
- 1750-8606
- OpenAlex
- W4313297029
- Cited by
- 27
- References
- 36
- Citations by year
- 2026: 5 · 2025: 14 · 2024: 6 · 2023: 2
- FWCI
- 11.86
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Child Development Perspectives (publishedVersion)
- Deep Blue (University of Michigan) (submittedVersion)
- Funders
- National Science Foundation (2115382)
- National Science Foundation of Sri Lanka (2115382)
- Topics
- Social Sciences › Education › Child Development and Digital Technology
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
- Keywords
- conversational technologies, human-machine interaction, chatbots, child development, early childhood, social interaction, artificial intelligence
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