Balancing AI Regulation: Comprehensive vs. Targeted Approach

Congress faces significant challenges in crafting AI legislation because of the technology's complexity and differing opinions around regulating it, said R Street Institute's Brandon Pugh.

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Some members of Congress have pushed for a comprehensive approach to regulating AI, similar to the European Union's AI Act, while others prefer targeting specific concerns such as deepfakes or election security, according to Pugh. Congress struggles with consensus around AI legislation because of a lack of clear definitions for basic concepts such as algorithms along with views on what should be done transcending party lines, he said (see: AI/ML's Role in Cybersecurity: Balancing Innovation, Safety).

"Many are not experts when it comes to AI, and I think to their credit, they've recognized that," Pugh said. "So it's a matter of learning, 'What do we need to do?' There's not actually even agreement around, 'What is an algorithm?' That sounds so basic, but that is key. So, I think we're in a learning phase."

In this video interview with Information Security Media Group at Black Hat 2024, Pugh also discussed:

• The increasing complexity for multiple industries due to inconsistent state-level AI regulations;
• The contrast between the EU's strict regulatory model and the lighter-touch approach in the U.S.;
• Why there's an urgent need for federal privacy laws to protect data used by AI systems.

Pugh previously served as a paratrooper and international law officer and is currently in the U.S. Army Reserve as a national security law professor at The Judge Advocate General's Legal Center and School. Before joining R Street, Pugh served in elected and appointed roles at the local, county and state level. He also managed a cyberwarfare publication and was a fellow with the Federal Bureau of Investigation.