Data‑Centric Governance And Ethical Frameworks For Trustworthy AI And Big Data Systems
Keywords:
Data governance, ethical AI, cloud analytics, compliance, transparency, trustworthy systems, big data ethicsAbstract
The rapid proliferation of artificial intelligence (AI), big data analytics, and cloud‑based data governance frameworks has catalyzed transformative changes across sectors including health, commerce, urban infrastructure, and scientific inquiry. Despite immense potential, such data‑driven technologies present complex ethical, regulatory, and governance challenges that require systematic theoretical and practical frameworks. This article critically explores the intersection of data governance, ethics, compliance, and trustworthiness in AI and big data ecosystems. Drawing on multidisciplinary scholarship and empirical insights, it synthesizes scholarly debate on responsible AI, scalable governance mechanisms, ethical data practices, and compliance strategies, while articulating novel theoretical linkages across these dimensions. Findings illustrate the need for robust data governance frameworks to address redundancy, quality, and ethical risks, while advocating for transparency, accountability, and alignment with societal values. Implications underscore how integrated governance approaches can enable trustworthy and socially beneficial AI systems. The article concludes with recommendations for future research and policy priorities in the ethical governance of AI and big data.
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