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

TL;DR

This systematic review analyzes privacy-by-design approaches for protecting youth in AI-enabled smart devices, highlighting technical solutions, policy gaps, and educational strategies, and proposes a multi-stakeholder model for more effective privacy ecosystems.

Contribution

It provides a comprehensive, empirically grounded analysis of existing privacy frameworks and offers actionable recommendations for youth-centered privacy design in smart devices.

Findings

Technical solutions like federated learning are underutilized.

Policy frameworks have enforcement gaps and lack age-specific design.

Educational initiatives are rarely integrated systematically.

Abstract

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.