National Security and Federalizing Data Privacy Infrastructure for AI Governance

Hu, Margaret, Behar, Eliott & Ottenheimer, Davi

Journal: Fordham Law Review

Volume: 92

First Page: 1829

Year: 2024

Bluebook Citation: 92 FORDHAM L. REV. 1829 (2024)

Author: Margaret Hu: all 17 publications


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.

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