Stanford Computational Antitrust
Episode 32: Cary Coglianese on the Use of AI in Public Enforcement
Mar 12, 2025
Cary Coglianese, the Edward B. Shils Professor of Law and Political Science at the University of Pennsylvania, dives into the intriguing world of AI in public enforcement. He discusses the shift in AI regulation from rigid 'guardrails' to more flexible 'leashes' that embrace innovation while ensuring safety. Coglianese addresses the balance of AI's efficiencies against ethical standards, highlighting the necessity of human oversight and the implications of recent regulatory developments, including the EU's Digital Markets Act.
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Quick takeaways
- The evolution of AI regulation advocates for flexible frameworks, favoring responsive 'leashes' over static 'guardrails' to balance innovation and safety.
- Proactive risk management strategies are essential for regulators to address antitrust issues related to AI, preventing violations before they occur.
Deep dives
Shifting Metaphors in AI Regulation
The concept of AI regulation is evolving from traditional fixed governance metaphors to more dynamic approaches. The distinction between 'guardrails' and 'leashes' is particularly significant; while guardrails imply static, protective measures, leashes suggest a responsive and flexible regulatory framework. This metaphor captures the inherent fluidity of AI technology, necessitating oversight that adapts to its rapid development. By viewing regulation as a 'leash,' there remains room for innovation while ensuring necessary human oversight, allowing AI to explore new avenues without straying into detrimental territory.
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