AI’s Big Future in Energy and Climate Regulation

Cary Coglianese, director of the Penn Program on Regulation, explores AI’s potential to help regulators keep pace with energy sector growth and climate-tech innovation.
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The ongoing transition to a cleaner energy system has positive implications for climate, energy security and equity. Yet the same transition poses myriad challenges for regulators, who are faced with an energy system that is more complex and distributed than ever, and where rapid innovation threatens to outpace their ability to tailor rules and effectively monitor compliance among a growing number of regulated entities.

Cary Coglianese, director of the Penn Program on Regulation, discusses the role that AI can play in optimizing regulation for an increasingly dynamic and innovative energy sector. Coglianese explores the role that AI might play in the development of rules and in measuring regulatory effectiveness. He also examines challenges related to AI energy consumption and bias that must be addressed if the technology’s potential as a regulatory tool is to be realized.

Cary Coglianese is director of the Penn Program on Regulation and a professor of law at the University of Pennsylvania.  

Professor Coglianese’s work discussed in this podcast includes the following papers he has published: “Deploying Machine Learning for a Sustainable Future,” “Optimizing Regulation for an Optimizing Economy,” “Regulating by Robot: Administrative Decision Making in the Machine-Learning Era,” “Transparency and Algorithmic Governance,” and “Procurement and Artificial Intelligence.”

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Energy Policy Now is produced by The Kleinman Center for Energy Policy at the University of Pennsylvania. For all things energy policy, visit kleinmanenergy.upenn.edu

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