系统梳理智能设备中青少年隐私保护方案，揭示技术主导、政策执行弱的现实问题。
Toward Youth-Centered Privacy-by-Design in Smart Devices: A Systematic Review
- 基于PRISMA流程筛选122篇文献，按技术、政策、教育三类分析
- 67%研究聚焦技术方案，但实际落地率低，政策执行存在漏洞
- 建议多方协同构建透明、可适配青少年的隐私保护生态
本研究采用PRISMA指南流程，系统评估过去十年间用于保护人工智能驱动智能设备中青少年隐私的隐私设计框架、工具与政策。从主要学术及灰色文献库中检索到2,216条记录，经去重和筛选后，645篇进入资格评估，最终122篇纳入分析。研究按技术解决方案、政策/监管措施、教育/意识策略三类主题组织。结果显示，尽管本地化处理、联邦学习和轻量加密等技术手段显著降低数据暴露风险，但其应用仍受限；欧盟GDPR、英国年龄适配设计规范、加拿大PIPEDA等政策虽提供重要基准，却存在执行不足和年龄适配义务缺失问题；而教育举措极少被系统性纳入课程。整体上，技术类研究占比达67%，政策类21%，教育类12%，凸显技术以外领域的实施缺口。为此，建议建立由政策制定者、制造商与教育者共同参与的多利益相关方模型，协同构建包容、透明且情境敏感的隐私保护体系。该研究通过实证洞察推动青少年数据保护讨论，为面向年轻用户的伦理化、隐私保护型AI系统设计提供可操作建议。
原文摘要 · Abstract (English)
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.
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