Socio-technical Imaginaries: Envisioning and Understanding AI Parenting Supports through Design Fiction
Open accessAbstract
How might emerging modalities (e.g., NLP) be leveraged to transform the provision of parenting support? To explore the role of AI technologies in supporting parenting behaviour—and child-well-being—we surveyed 92 parents to gather their perspectives on nine future-oriented scenarios. We used Design Fiction and Speed Dating to understand parents needs and preferences around the design of agent-based supports. We explore the perceived benefits of AI assistants (i.e., receiving objective feedback, managing emotions and personalised guidance) and the most voiced concerns (i.e., AI undermining parental authority, replacing human interactions, and promoting lazy parenting). Finally, we highlight a number of plausible design directions based on the scenarios that parents were positive about.
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GAI offers promising support for parents by enhancing their ability to educate and engage with their children.
“GAI offers promising support for parents by enhancing their ability to educate and engage with their children.”
From SET-PAiREd: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot (2025) · cites this paper as [61]
AI-driven systems can support parenting education and provide evidence-based advice through applications and chatbots, delivering micro-interventions.
“Prior work suggested that AI-driven systems can support parenting education [61] and provide evidence-based advice through applications and chatbots, delivering micro-interventions such as teaching parents how to praise their children effectively [11, 17] or offering strategies to teach complex concepts [55, 69].”
From SET-PAiREd: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot (2025) · cites this paper as [61]
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References 359 · Cited by 35
Research works printed but not linked: 9
- Amit Baumel, Aditya Pawar, John M. Kane, and Christoph U. Correll. 2016. Digital Parent Training for Children with Disruptive Behaviors: Systematic Review and Meta-Analysis of Randomized Trials. Journal of Child and Adolescent Psychopharmacology 26, 8 (2016), 740-749. https://doi.org/10.1089/cap.2016. 0048 · DOI
- D Baumrind. 1967. Child care practices anteceding three patterns of preschool behavior. Genetic psychology monographs 75, 1 (1967), 43-88.
- Anthony Dunne and Fiona Raby. 2013. Speculative Everything : Design, Fiction, and Social Dreaming. The MIT Press. https://readings.design/PDF/speculative- everything.pdf
- David P Farrington. 2007. Childhood risk factors and risk-focused prevention. The Oxford handbook of criminology, Vol. 4.
- Ascan F Koerner, Paul Schrodt, and Mary Anne Fitzpatrick. 2017. Engaging Theories in Family Communication. (2017), 142-153. https://doi.org/10.4324/ 9781315204321-13 · DOI
- Patty Leijten, Frances Gardner, G.J. Melendez-Torres, Jolien van Aar, Judy Hutchings, Susanne Schulz, Wendy Knerr, and Geertjan Overbeek. 2019. Meta- Analyses: Key Parenting Program Components for Disruptive Child Behavior. Journal of the American Academy of Child & Adolescent Psychiatry 58, 2 (2019), 180-190. https://doi.org/10.1016/j.jaac.2018.07.900 · DOI
- Laura Pina, Kael Rowan, Asta Roseway, Paul Johns, Gillian R. Hayes, and Mary Czerwinski. 2014. Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth '14. Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare (2014), 17-24. https://doi.org/10.4108/icst.pervasivehealth.2014.254958 · DOI
- Ben Shneiderman. 2022. Human-Centered AI. (2022), 17-24. https://doi.org/10. 1093/oso/9780192845290.003.0002 · DOI
- Kieran Woodward, Eiman Kanjo, David J. Brown, T. M. McGinnity, Becky Inkster, Donald J. Macintyre, and Athanasios Tsanas. 2022. Beyond Mobile Apps: A Survey of Technologies for Mental Well-Being. IEEE Transactions on Affective Computing 13, 3 (2022), 1216-1235. https://doi.org/10.1109/taffc.2020.3015018 · DOI · Paper page
- Authors
- Petsolari, M., Ibrahim, S. B., & Slovak, P.
- Affiliations
- King's College London (GB)
- Department of Informatics, King's College London, United Kingdom
- Venue
- Proceedings of the CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2024-05-11
- Pages
- 1-27
- OpenAlex
- W4396833254
- Cited by
- 35
- References
- 359
- Citations by year
- 2026: 19 · 2025: 16
- FWCI
- 11.28
- Type
- conference paper
- Language
- en
- Open access
- green
- kclpure.kcl.ac.uk
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Research Portal (King's College London) (submittedVersion, cc-by)
- Funders
- UKRI Future Leaders Fellowship (MR/T041897/1)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- design fiction, sociotechnical imaginaries, parents' perspectives, AI assistants, child well-being, parental authority, future scenarios, natural language processing, human-AI interaction
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