Does an AI creation reflect my teenager’s culture and intentions?
Sophie Dallison; Bianca Moffett; Princess Makhubela; Tamera Nkuna; Julia R Pozuelo; Alastair van Heerden; Heather O'Mahen; Amaryllis Mavragani · 2025-12-05 · Journal of Medical Internet Research
Adolescents aged 15–19 yearsCC BY 4.0Generative text/image AI and algorithmic music generation; supervised workshopsChild-facing evidence
Would our child’s future opportunities be shaped by an AI interpretation of my speech?
Zoë Firth; Christine Aicardi; Stephen Oram; Nicholas Cummins; Alice Wickersham; Helen L Fisher; Johnny Downs · 2025-11-12 · Child and Adolescent Mental Health
Young people aged 13–18 years, plus parents of autistic childrenCC BY 4.0Proposed speech/NLP predictive AI; speculative-story consultationDirect parenting evidence
Has an autism assessment model been checked for children like ours?
Aaron J Kaat; Ashlynn Campagna; Hannah Feiner; Jeffrey Michael Grauzer; Amanda Nicole Hobson; Maranda Jones; Jordan Paige Lee; Laura Jean Sudec; Megan York Roberts · 2026-08-04 · JCPP Advances
Toddlers aged 15–36 months; mean 30.4 monthsCC BY 4.0Narrow interpretable predictive classification; not generative AIFamily implications
What should we ask when an AI tool is said to be fair for children?
Elizabeth A. Campbell; Saurav Bose; Aaron J. Masino · 2024-10-23 · PLOS Digital Health
Pediatric patients in a US hospital system; exact age span not specified in this curationCC BY 4.0Narrow EHR-based predictive models; subgroup performance auditFamily implications
What does our school’s AI monitoring see outside the classroom?
Alison O'Daffer; Wendy Liu; Cinnamon S Bloss · 2025-07-08 · Journal of Medical Internet Research
Middle- and high-school students; no student participantsCC BY 4.0Commercial automated surveillance/AI claims; no model performance validationChild-facing evidence
Who decides what a child-friendly AI robot should look and feel like?
Gema Benedicto Rodríguez; Vanessa Zorrilla-Muñoz; Carlos G Juan; Jose Manuel Ferrandez · 2026-08-07 · Frontiers in Robotics and AI
Autistic children aged 3–14 and neurotypical children aged 6–15CC BY 4.0Social-robot design analysis; no autonomous-system or LLM trialChild-facing evidence
How would our family be involved if an algorithm flagged a young person’s risk?
Rohan R Dayal; Pua Lani Yang; Laura Nicole Sisson; Mira Bajaj; Shannon Archuleta; Sophie Yao; Daniel H Park; Hanae Fujii-Rios; Emily E Haroz; Andrew Coristine · 2025-08-19 · Journal of Medical Internet Research
Patient interview ages 8–25 years; limited representation under eighteenCC BY 4.0Proposed narrow EHR risk prediction; stakeholder implementation evidenceFamily implications
Could a prediction about my child’s future wishes outweigh what they say now?
Dominic James Clifford Wilkinson; Julian Savulescu; Brian Earp · 2026-09-09 · Neuroethics
Children and adolescents with different present/future decision-making capacitiesCC BY 4.0Hypothetical narrow AI preference prediction; normative analysisFamily implications
Is this AI helping our family or turning my child into a stream of scores?
Yan Xu; Hang Chen; Mu-Mu Wei; Yi Zhang; Hong-Tao Cui; Fang Liu · 2026-02-17 · Frontiers in Psychology
Early childhood, especially neurotypical children in consumer home settingsCC BY 4.0Consumer predictive/monitoring AI and hypothetical caregiver assistantsDirect parenting evidence
What should happen to the traces my teenager leaves while using a health app?
Alison Giovanelli; Jonathan Rowe; Madelynn Taylor; Mark Berna; Kathleen P Tebb; Carlos Penilla; Marianne Pugatch; James Lester; Elizabeth M Ozer; Tiffany Leung; Nicole Levitz; Yaltafit Jeem; Nicos Maglaveras · 2023-05-24 · Journal of Medical Internet Research
Adolescents, illustrated through alcohol-risk behavior intervention designCC BY 4.0Mixed proposed predictive AI and content-generation roles; conceptual designChild-facing evidence
Were children like mine represented in the data behind this cancer AI tool?
Alberto Eugenio Tozzi; Ileana Croci; Paul Voicu; Francesco Dotta; Giovanna Stefania Colafati; Andrea Carai; Francesco Fabozzi; Giuseppe Lacanna; Roberto Premuselli; Angela Mastronuzzi · 2023-10-27 · Frontiers in Oncology
Pediatric brain-tumor cohorts; twenty included studies also used adult dataCC BY 4.0Mixed narrow predictive/imaging AI; dataset evidence reviewFamily implications
Who gains access to the benefits of child-health AI, and who helps design it?
Vijaytha Muralidharan; Joel Schamroth; Alaa Youssef; Leo A Celi; Roxana Daneshjou; Walter Karlen · 2024-08-22 · PLOS Digital Health
Children and young people in high- and lower-resource health systemsCC BY 4.0Mixed narrow healthcare AI/ML; narrative equity analysisFamily implications
Could this AI imaging service work fairly for families outside well-resourced hospitals?
Rutger A. J. Nievelstein; Amit Gupta; Joanna Kasznia-Brown; Nasreen Mahomed; Jaishree Naidoo; Marla B. K. Sammer · 2026-07-23 · Pediatric Radiology
Children receiving imaging, especially in low- and middle-income settingsCC BY 4.0Narrow imaging AI/ML; consensus-based equity frameworkFamily implications
What should our family know before a child’s surgery or recordings involve AI?
A Anand; CK Sinha · 2026-02-23 · Annals of The Royal College of Surgeons of England
Children undergoing surgery and adolescents with evolving decision capacityCC BY 4.0Mixed narrow surgical AI and adaptive systems; normative legal reviewFamily implications
What should happen if an AI study changes after our child has enrolled?
Chih-Shung Wong; Tsui-Wen Hsu · 2026-03-27 · Frontiers in Digital Health
Pediatric AI research; worked example describes speech therapy ages 3–7CC BY 4.0AI pediatric-trial governance proposal; no model or outcome trialFamily implications
Children and adolescents with ADHD across home, school, and clinic settingsCC BY 4.0Mixed AI therapy-chatbot designs and adaptive systems; policy analysisChild-facing evidence
What happens to private information a teenager shares with an AI companion?
Kunmi Sobowale; Daniel Kevin Humphrey; Sophia Yingruo Zhao; John Torous · 2025-12-10 · JMIR Mental Health
Youth-targeted platforms; raters used simulated youth personas rather than child participantsCC BY 4.0Direct-to-consumer generative AI/LLM companions; simulated-user quality auditChild-facing evidence