Nicholas Reese, co-founder and COO of Frontier Foundry, former director of Emerging Technology at the Department of Homeland Security (2019-2023) and contributor to the Center for Governance and Technology and Systems (GoTech) Insights blog, recently shared his expertise with Business Insider on how different presidential administrations might approach AI policy and regulation. The article examined the potential impact of either a Trump or Harris presidency on the future of artificial intelligence policy in the United States.
Drawing from his unique perspective as someone who served in the Department of Homeland Security during the Trump administration, Reese offered valuable insights into the historical approach to AI policy and potential future directions. He noted that contrary to common perception, the Trump administration was "very active" on AI initiatives, particularly in developing "trustworthy principles for trustworthiness and AI." Reese characterized the Trump administration's approach as "incremental."
Regarding future policy directions, Reese highlighted potential challenges that could arise from Trump's stated intention to repeal Biden's executive orders on AI. He suggested this could create uncertainty among innovators in the field. Looking at a potential Harris administration, Reese predicted a more predictable approach, noting that it would likely follow a "much more linear, much more predictable path that is based on a lot of the existing corpus of AI policies."
As an adjunct professor at New York University with significant experience in government technology policy, Reese also provided context on existing regulatory frameworks. He explained that the controversy around Biden's executive order wasn't about regulation per se but rather about creating a "big, monolithic AI regulation," noting that regulation already exists within various industries.
Reese's insights in the Business Insider Article reflect the complex interplay between political leadership and technological innovation, highlighting the importance of balanced, informed approaches to AI policy development.
