Since Greg Lambert is on vacation, we wanted to share an episode of Future Ready Business podcast, which Greg also produces. Art Cavazos and Courtney White from Jackson Walker, LLP, interview Neil Chilson, Head of AI Policy at the Abundance Institute, and Travis Wussow,

Neil Chilson and Travis Wussow both emphasize the complexity of regulating AI due to its broad applications and the difficulty in defining it. They argue that most AI applications fall into areas that already have existing regulatory frameworks, such as healthcare, intellectual property, and transportation. Chilson suggests that policymakers should focus on identifying specific harms and addressing gaps in current regulations rather than creating entirely new frameworks for AI.

Regarding current AI policy, Wussow notes that litigation is already underway, particularly in areas like copyright infringement. He believes that proactive policymaking will likely wait until these legal disputes are resolved. Chilson highlights that there is significant activity at the federal level, with the White House issuing a comprehensive executive order on AI, and at the state level, with numerous AI-related bills being proposed.

On the topic of AI's potential impact on elections and misinformation, Chilson expresses less concern about AI-generated content itself and more about the distribution networks that spread misinformation. He emphasizes the importance of maintaining trust in the electoral system and suggests that tracking and analyzing actual instances of AI use in elections is crucial for understanding its real impact.

Looking to the future, both experts stress the importance of the United States maintaining its leadership in AI development. They argue that this leadership is essential for embedding American values into AI systems and preventing other countries, such as China, from dominating the field with potentially restrictive approaches. Chilson also highlights the potential for AI to revolutionize healthcare, emphasizing the need to adapt regulatory frameworks, particularly in areas like FDA approval processes, to allow for the benefits of AI-driven personalized medicine while ensuring safety and efficacy.

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