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Enhancing a Sustainable Future with Music in Early Childhood ECME 2024
  • ISSN: 2516-1989
  • E-ISSN: 2516-1997

Abstract

This comprehensive review explores AI’s transformative potential in assisting parent–infant musical interactions, a critical component of early child development. The article explored multifaceted applications of AI within this domain, including personalized music recommendations, interactive learning platforms and dynamic assessment tools. It shows how AI can enable emotional bonding, optimize the musical environment and help understand infants’ developmental needs. However, the review also recognizes the ethical challenges and potential risks associated with AI integration, such as the potential for reduced authentic interaction, algorithmic biases and data security issues. Mitigating these challenges requires strong ethical frameworks and regulatory mechanisms around data ownership, algorithmic fairness and product safety. Ultimately, AI’s role in early childhood music education needs to be rigorously bounded: its technical functions (e.g. real-time feedback, content curation) should support, not overshadow, the irreplaceable human capacity for emotional attunement. Thus, ethical AI design should demarcate its operational scope to avoid conflating technical efficiency with emotional intimacy.

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2025-11-15
2026-04-11

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Keyword(s): AI; algorithmic bias; assistive AI technology; ethical AI; home musical environment; infant development; interactive music systems

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