# Investigation of the Privacy Concerns in AI Systems for Young Digital Citizens: A Comparative Stakeholder Analysis

arXiv: https://arxiv.org/abs/2501.13321 · HTML: https://mlsanity.com/paper/2501.13321/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 59 references that are in the map.
- First posted on arXiv 23 Jan 2025.

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

- [From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy](https://mlsanity.com/paper/2307.00691/) (2023)
- [Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliance](https://mlsanity.com/paper/2207.01482/) (2022)
- [User Acceptance of Usable Blockchain-Based Research Data Sharing System: An Extended TAM Based Study](https://mlsanity.com/paper/2001.00079/) (2019)

## Built on by (most cited first, 1 of 1)

- [Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AI](https://mlsanity.com/paper/2503.11950/) (2025)

## Abstract (arXiv)

The integration of Artificial Intelligence (AI) systems into technologies used by young digital citizens raises significant privacy concerns. This study investigates these concerns through a comparative analysis of stakeholder perspectives. A total of 252 participants were surveyed, with the analysis focusing on 110 valid responses from parents/educators and 100 from AI professionals after data cleaning. Quantitative methods, including descriptive statistics and Partial Least Squares Structural Equation Modeling, examined five validated constructs: Data Ownership and Control, Parental Data Sharing, Perceived Risks and Benefits, Transparency and Trust, and Education and Awareness. Results showed Education and Awareness significantly influenced data ownership and risk assessment, while Data Ownership and Control strongly impacted Transparency and Trust. Transparency and Trust, along with Perceived Risks and Benefits, showed minimal influence on Parental Data Sharing, suggesting other factors may play a larger role. The study underscores the need for user-centric privacy controls, tailored transparency strategies, and targeted educational initiatives. Incorporating diverse stakeholder perspectives offers actionable insights into ethical AI design and governance, balancing innovation with robust privacy protections to foster trust in a digital age.