CYAIMar 15, 2025

Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AI

arXiv:2503.11950v312 citationsh-index: 6Syst.
Originality Synthesis-oriented
AI Analysis

It addresses privacy governance in AI for stakeholders like young users and professionals, but is incremental as it builds on existing ethical frameworks.

This study explored privacy concerns among digital citizens, parents/educators, and AI professionals, revealing distinct expectations like autonomy for youth and regulatory oversight for adults, and developed the PEA-AI model to structure privacy decision-making as stakeholder negotiation.

The increasing integration of Artificial Intelligence (AI) in digital ecosystems has reshaped privacy dynamics, particularly for young digital citizens navigating data-driven environments. This study explores evolving privacy concerns across three key stakeholder groups, digital citizens (ages 16-19), parents/educators, and AI professionals, and assesses differences in data ownership, trust, transparency, parental mediation, education, and risk-benefit perceptions. Employing a grounded theory methodology, this research synthesizes insights from 482 participants through structured surveys, qualitative interviews, and focus groups. The findings reveal distinct privacy expectations: Young users emphasize autonomy and digital freedom, while parents and educators advocate for regulatory oversight and AI literacy programs. AI professionals, in contrast, prioritize the balance between ethical system design and technological efficiency. The data further highlights gaps in AI literacy and transparency, emphasizing the need for comprehensive, stakeholder-driven privacy frameworks that accommodate diverse user needs. Using comparative thematic analysis, this study identifies key tensions in privacy governance and develops the novel Privacy-Ethics Alignment in AI (PEA-AI) model, which structures privacy decision-making as a dynamic negotiation between stakeholders. By systematically analyzing themes such as transparency, user control, risk perception, and parental mediation, this research provides a scalable, adaptive foundation for AI governance, ensuring that privacy protections evolve alongside emerging AI technologies and youth-centric digital interactions.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes