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

arXiv: https://arxiv.org/abs/2503.11950 · HTML: https://mlsanity.com/paper/2503.11950/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 47 references that are in the map.
- First posted on arXiv 15 Mar 2025.

## Builds on (most cited first, 3 of 3)

- [Navigating AI to Unpack Youth Privacy Concerns: An In-Depth Exploration and Systematic Review](https://mlsanity.com/paper/2412.16369/) (2024)
- [Toward Ethical AI: A Qualitative Analysis of Stakeholder Perspectives](https://mlsanity.com/paper/2501.13320/) (2025)
- [Investigation of the Privacy Concerns in AI Systems for Young Digital Citizens: A Comparative Stakeholder Analysis](https://mlsanity.com/paper/2501.13321/) (2025)

## Built on by (most cited first, 5 of 5)

- [Covert Surveillance in Smart Devices: A SCOUR Framework Analysis of Youth Privacy Implications](https://mlsanity.com/paper/2510.24072/) (2025)
- [Convenience vs. Control: A Qualitative Study of Youth Privacy with Smart Voice Assistants](https://mlsanity.com/paper/2601.04399/) (2026)
- [Balancing Usability and Compliance in AI Smart Devices: A Privacy-by-Design Audit of Google Home, Alexa, and Siri](https://mlsanity.com/paper/2601.04403/) (2026)
- [Toward Youth-Centered Privacy-by-Design in Smart Devices: A Systematic Review](https://mlsanity.com/paper/2601.11598/) (2026)
- [Negotiating Privacy with Smart Voice Assistants: Risk-Benefit and Control-Acceptance Tensions](https://mlsanity.com/paper/2604.06235/) (2026)

## Abstract (arXiv)

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-young digital citizens, 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 key participants through structured surveys, qualitative interviews, and focus groups to identify distinct privacy expectations. Young digital citizens emphasized autonomy and digital agency, while parents and educators prioritized oversight and AI literacy. AI professionals focused on balancing ethical design with system performance. The analysis revealed significant gaps in transparency and digital literacy, underscoring the need for inclusive, stakeholder-driven privacy frameworks. Drawing on comparative thematic analysis, this study introduces the Privacy-Ethics Alignment in AI (PEA-AI) model, which conceptualizes privacy decision-making as a dynamic negotiation among stakeholders. By aligning empirical findings with governance implications, this research provides a scalable foundation for adaptive, youth-centered AI privacy governance.