Pith. sign in

REVIEW 1 cited by

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

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2501.13321 v1 pith:DKVE7ROH submitted 2025-01-23 cs.CY cs.AI

classification cs.CYcs.AI
keywords dataprivacytransparencytrustanalysisconcernsdigitalownership
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Digital Privacy Everywhere

    cs.CR 2025-06 reject novelty 3.0 of 10

    A patent-style description of a device-privacy enforcement architecture, with qualitative prototype claims and no reproducible evaluation.

Pith tools