Cary Coglianese, director of the Penn Program on Regulation, discusses AI’s potential in optimizing energy regulation and measuring its effectiveness. Topics include managing a complex energy grid, challenges of regulating distributed energy sources, AI in forecasting energy demand and detecting methane leaks, and assessing regulation and algorithm transparency. The podcast also explores the balance between AI's energy consumption and renewable energy development.
AI can optimize regulation in the evolving energy sector by forecasting demand, detecting violations, and assessing effectiveness.
Transparency and energy consumption are challenges to overcome in integrating AI into energy regulation.
Deep dives
Increasing complexity of the energy system
The energy system is becoming more complex and interconnected due to the growing number of diverse power sources, including renewable and distributed resources. The rise of climate change and environmental concerns, as well as the increased frequency of storms and wildfires, add further complexity to the energy and environmental context.
The role of AI in regulation
AI can help regulators keep pace with the evolving energy sector by optimizing resources and identifying regulatory targets. Machine learning algorithms can be used to forecast energy demand, manage the flow of paperwork, detect regulatory violations, and allocate inspection resources more effectively. AI can also be valuable in understanding supply chains and assessing regulatory effectiveness.
Transparency and energy consumption considerations
Transparency is a challenge with AI algorithms, as they can be complex black box systems. Efforts are being made to improve transparency, but it's crucial to ensure that government contracts for AI tools necessitate providing a modicum of information to sustain their use and address any challenge. Another concern is the energy consumption of AI, particularly large language models, which require significant computing power. Striking a balance between the positive benefits of AI and its potential energy demands is a challenge for society.
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. ---
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.
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