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Sam Hammond

Chief economist at the Foundation for American Innovation. Brings an innovation-first perspective to the AI conversation.

Top 3 podcasts with Sam Hammond

Ranked by the Snipd community
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160 snips
Jun 12, 2025 • 48min

The Narrow Path: Sam Hammond on AI, Institutions, and the Fragile Future

In this engaging discussion, Sam Hammond, Chief Economist at the Foundation for American Innovation, offers an innovative perspective on the dual realities posed by AI development. He delves into the urgent need for responsible governance to prevent dystopian outcomes and highlights the fragility of our institutions amid rapid technological change. Topics include the contrast between private and public sector adaptations, the necessity for adaptive regulatory frameworks, and the importance of global coordination to ensure AI empowers humanity rather than controlling it.
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28 snips
May 22, 2025 • 18min

The ‘big, beautiful bill' to ban state AI laws

In this discussion, Sam Hammond, Chief Economist at the Foundation for American Innovation, dives into the controversial proposal to ban state-level AI regulations for a decade. He shares insights on how this moratorium could reshape the AI landscape amid a global tech race, especially against competitors like China. The conversation critiques the existing regulatory challenges and highlights the urgent need for a unified federal framework to tackle AI's rapid evolution while balancing industry interests and safety concerns.
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Jul 11, 2025 • 41min

Inside AI Policy with FAI’s Chief Economist Sam Hammond

Sam Hammond, Chief Economist at the Foundation for American Innovation, dives into AI policy and its rapid evolution. He discusses the crucial infrastructure needed for AI development and the legislative responses to keep pace with technology. Sam highlights the complexities of fair use regarding AI training data and emphasizes the urgent need for effective regulation. He also addresses the looming labor market disruptions caused by AI, advocating for innovative policy solutions while maintaining an optimistic outlook on future advancements in AI.

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