Abstract
This Essay contends that data infrastructure, when implemented on a national scale, can transform the way we conceptualize artificial intelligence (AI) governance. AI governance is often viewed as necessary for a wide range of strategic goals, including national security. It is widely understood that allowing AI and generative AI to remain self-regulated by the U.S. AI industry poses significant national security risks. Data infrastructure and AI oversight can assist in multiple goals, including: maintaining data privacy and data integrity; increasing cybersecurity; and guarding against information warfare threats. This Essay concludes that conceptualizing data infrastructure as a form of critical infrastructure can reinforce domestic national security strategies. With the growing threat of AI weaponry and information warfare, data privacy and information security are core to cyber defense and national security. Data infrastructure can be seen as an integrated critical infrastructure strategy in constructing AI governance legally and technically.
Document Type
Article
Publication Date
2024
Publication Information
92 Fordham Law Review 1829-1853 (2024)
Repository Citation
Hu, Margaret; Behar, Eliott; and Ottenheimer, Davi, "National Security and Federalizing Data Privacy Infrastructure for AI Governance" (2024). Faculty Publications. 2166.
https://scholarship.law.wm.edu/facpubs/2166
Comments
Written for the symposium The New AI: The Legal and Ethical Implications of ChatGPT and Other Emerging Technologies (2023) at Fordham University School of Law.