Global Trends in Data and Artificial Intelligence Governance
Keywords:
data governance, artificial intelligence, digital ethics, technology policy, algorithmic transparency, data justiceAbstract
Objective: This study aims to systematically analyze global trends in data and artificial intelligence (AI) governance with an emphasis on policy, ethical, and technological dimensions.
Methods and Materials: This qualitative review employed a systematic literature review and thematic analysis approach. Data were collected from international databases such as Scopus, Web of Science, and Google Scholar. Twelve articles with strong conceptual relevance to the topic were selected based on theoretical saturation. Data were analyzed using Nvivo version 14 through open, axial, and selective coding to identify major themes and conceptual relationships.
Findings: The findings revealed that global data and AI governance are evolving in three main dimensions: (1) reconfiguration of policy and institutional structures from centralized regulation to multi-level, network-based governance; (2) reinforcement of ethical and legal frameworks emphasizing transparency, data justice, and algorithmic accountability; and (3) emergence of technological challenges resulting from the convergence of new technologies and the need for adaptive governance. The analysis highlighted that successful AI governance depends on international cooperation, technological diplomacy, and the enhancement of public trust.
Conclusion: The study concludes that the future of data and AI governance requires adaptive, interdisciplinary, and ethics-driven frameworks capable of balancing technological innovation, digital security, and social justice. Strengthening regulatory institutions, enhancing algorithmic transparency, and establishing global standards are essential to achieving intelligent and sustainable governance.
Downloads
References
Binns, R. (2022). Fairness in machine learning: Lessons from political philosophy. Oxford University Press.
Bryson, J. (2022). AI governance: A research agenda. Cambridge University Press.
Buchanan, B. (2023). The new fire: War, peace, and democracy in the age of AI. MIT Press.
Cath, C. (2023). Governing artificial intelligence ethically: Global challenges and frameworks. Springer.
Cave, S., & Dignum, V. (2021). AI governance: Responsibility and accountability in machine learning systems. Nature Machine Intelligence, 3(6), 512–520.
Coeckelbergh, M. (2022). AI ethics. MIT Press.
Floridi, L. (2022). Ethics, governance, and policy for AI. Springer.
Hacker, P. (2022). A legal framework for AI accountability. European Law Journal, 28(3), 317–339.
Jobin, A. (2021). Ethical frameworks for AI: Comparative analysis of global principles. AI & Society, 36(2), 411–425.
Kuner, C. (2022). Transborder data flows and data sovereignty. Oxford Journal of Legal Studies, 42(1), 91–116.
Leslie, D. (2023). Ethics of AI: Balancing fairness, accountability, and transparency. Cambridge University Press.
Mittelstadt, B. (2023). The ethics of AI governance: Challenges and pathways. AI Ethics, 3(1), 22–39.
Stix, C. (2024). AI for sustainability: Governance perspectives. Journal of Responsible AI, 2(1), 45–63.
Taddeo, M., & Floridi, L. (2022). How AI governance can support resilience in digital societies. Philosophy & Technology, 35(4), 87–102.
UNESCO. (2021). Recommendation on the ethics of artificial intelligence. Paris: UNESCO.
van den Hoven, J. (2021). Data governance and the future of democratic accountability. Ethics and Information Technology, 23(2), 189–204.
