Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AI
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, paren...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-06-01
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| Series: | Systems |
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| Online Access: | https://www.mdpi.com/2079-8954/13/6/455 |
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| author | Ankur Barthwal Molly Campbell Ajay Kumar Shrestha |
| author_facet | Ankur Barthwal Molly Campbell Ajay Kumar Shrestha |
| author_sort | Ankur Barthwal |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c9496a50774c42cbb76f0eb82ce0857f |
| institution | Kabale University |
| issn | 2079-8954 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj-art-c9496a50774c42cbb76f0eb82ce0857f2025-08-20T03:26:52ZengMDPI AGSystems2079-89542025-06-0113645510.3390/systems13060455Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AIAnkur Barthwal0Molly Campbell1Ajay Kumar Shrestha2Computer Science Department, Vancouver Island University, Nanaimo, BC V9R 5S5, CanadaComputer Science Department, Vancouver Island University, Nanaimo, BC V9R 5S5, CanadaComputer Science Department, Vancouver Island University, Nanaimo, BC V9R 5S5, CanadaThe 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.https://www.mdpi.com/2079-8954/13/6/455privacyartificial intelligenceyouthPEA-AIdata ownershiptransparency |
| spellingShingle | Ankur Barthwal Molly Campbell Ajay Kumar Shrestha Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AI Systems privacy artificial intelligence youth PEA-AI data ownership transparency |
| title | Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AI |
| title_full | Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AI |
| title_fullStr | Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AI |
| title_full_unstemmed | Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AI |
| title_short | Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AI |
| title_sort | privacy ethics alignment in ai a stakeholder centric framework for ethical ai |
| topic | privacy artificial intelligence youth PEA-AI data ownership transparency |
| url | https://www.mdpi.com/2079-8954/13/6/455 |
| work_keys_str_mv | AT ankurbarthwal privacyethicsalignmentinaiastakeholdercentricframeworkforethicalai AT mollycampbell privacyethicsalignmentinaiastakeholdercentricframeworkforethicalai AT ajaykumarshrestha privacyethicsalignmentinaiastakeholdercentricframeworkforethicalai |