Data Privacy Frameworks for AI-Driven Social Media Moderation Tools
Keywords:
Data Privacy, AI, Social Media Moderation, GDPR, Privacy-by-Design, Adaptive AI Governance, Ethical AI, Author Name, Scopus, Springer, Journal Name, Wissira, Journal Short Form, Wissira Press, Wissira Research Lab, Research Gate, SSRN, ISSN, Academia, UGC Care, PubMed, WOSAbstract
The rise of artificial intelligence (AI)-driven tools for social media moderation has enhanced the ability to monitor, filter, and address harmful content efficiently. However, the increased reliance on AI raises critical concerns about data privacy, including user data collection, storage, and usage. This study examines prominent data privacy frameworks applicable to AIdriven social media moderation tools, assessing their effectiveness in mitigating privacy risks while maintaining moderation efficacy. Key aspects include an analysis of legal, ethical, and technical safeguards, with insights into existing frameworks like GDPR, CCPA, and AI-specific guidelines. The study proposes a hybrid framework integrating privacy-by-design principles and adaptive AI governance mechanisms to balance user privacy with robust content moderation.
