From "quantifying the child" to "supporting the caregiver": a paradigm evaluation and ethical pathway selection for

Yan Xu1,2, Hang Chen1,2, Mu-Mu Wei1,2

  • 1Department of Pediatrics, First Affiliated Hospital, Henan University of Chinese Medicine, Zhengzhou, Henan, China.

PubMed

Insights

Artificial Intelligence (AI) can support child development by assisting caregivers, not by quantifying children. Shifting to a caregiver support model reduces stress and enhances responsive parenting for better outcomes.

Area of Science:

  • Pediatric Care
  • Developmental Science
  • Human-Computer Interaction

Background:

  • Artificial Intelligence (AI) is increasingly used in pediatric care, with clinical tools aiding neurodevelopmental risk identification.
  • A growing trend involves consumer-grade technologies for continuous quantification of neurotypical children.

Purpose of the Study:

  • Critically evaluate the "Quantified Child" paradigm.
  • Propose an alternative AI application model for non-clinical settings.
  • Examine the risks and benefits of AI in early childhood development.

Main Methods:

  • Literature review and critical analysis of current AI trends in pediatrics.
  • Drawing on developmental science principles.
  • Conceptualizing a new AI paradigm focused on caregiver support.

Main Results:

  • The "Quantified Child" paradigm presents systemic risks, including technoference, caregiver anxiety, and iatrogenic effects from false positives.
  • AI as an administrative assistant for caregivers can reduce cognitive load and automate logistics.
  • Reducing caregiver stress and saving time are key mediators for positive child outcomes.

Conclusions:

  • A shift to a "Supporting the Caregiver" paradigm is recommended for non-clinical AI applications.
  • AI should reduce caregiver burden, indirectly enhancing responsive parenting.
  • This approach offers a more ethical and effective use of AI in early childhood.
Abstract

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