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Toward Youth-Centered Privacy-by-Design in Smart Devices: A Systematic Review

arXiv 2601.11598 ↗First posted 7 Jan 2026cs.CY cs.AI cs.HCcited by 0

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Abstract (arXiv)

This literature review evaluates privacy-by-design frameworks, tools, and policies intended to protect youth in AI-enabled smart devices using a PRISMA-guided workflow. Sources from major academic and grey-literature repositories from the past decade were screened. The search identified 2,216 records; after deduplication and screening, 645 articles underwent eligibility assessment, and 122 were included for analysis. The corpus was organized along three thematic categories: technical solutions, policy/regulatory measures, and education/awareness strategies. Findings reveal that while technical interventions such as on-device processing, federated learning, and lightweight encryption significantly reduce data exposure, their adoption remains limited. Policy frameworks, including the EU's GDPR, the UK Age-Appropriate Design Code, and Canada's PIPEDA, provide important baselines but are hindered by gaps in enforcement and age-appropriate design obligations, while educational initiatives are rarely integrated systematically into curricula. Overall, the corpus skews toward technical solutions (67%) relative to policy (21%) and education (12%), indicating an implementation gap outside the technical domain. To address these challenges, we recommend a multi-stakeholder model in which policymakers, manufacturers, and educators co-develop inclusive, transparent, and context-sensitive privacy ecosystems. This work advances discourse on youth data protection by offering empirically grounded insights and actionable recommendations for the design of ethical, privacy-preserving AI systems tailored to young users.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 126 references that are in the map. First posted on arXiv 7 Jan 2026.

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11 of 126 references.

References · 11

  1. 2021Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challengescited by 16
  2. 2018Security, Privacy and Safety Risk Assessment for Virtual Reality Learning Environment Applicationscited by 5
  3. 2024Navigating AI to Unpack Youth Privacy Concerns: An In-Depth Exploration and Systematic Reviewcited by 5
  4. 2025Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AIcited by 5
  5. 2015Privacy by design in big data: An overview of privacy enhancing technologies in the era of big data analyticscited by 4
  6. 2022RL-DistPrivacy: Privacy-Aware Distributed Deep Inference for low latency IoT systemscited by 4
  7. 2025Covert Surveillance in Smart Devices: A SCOUR Framework Analysis of Youth Privacy Implicationscited by 3
  8. 2025Toward Ethical AI: A Qualitative Analysis of Stakeholder Perspectivescited by 2
  9. 2025Ethical AI for Young Digital Citizens: A Call to Action on Privacy Governancecited by 2
  10. 2016Privacy of the Internet of Things: A Systematic Literature Review (Extended Discussion)cited by 1
  11. 2025Towards Resilience and Autonomy-based Approaches for Adolescents Online Safetycited by 1

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