AI-driven Economics using the AI Economist and WarpDrive
Solving global challenges, such as economic inequality and sustainability, requires new tools and data to design effective economic policies. The AI Economist is a reinforcement learning (RL) framework that outperforms and overcomes key limitations of traditional policy design methods. I will survey key results and systems that move this towards real world scale: 1) AI tax policies can significantly improve equality and productivity, 2) AI policies improve health and economic outcomes in simulated pandemics, 3) extensions to consumer-firm economies, more human-like agents, and AI pricing in platform businesses, and 4) WarpDrive, our open-source GPU framework for superfast multi-agent RL,
Stephan Zheng (www.stephanzheng.com) leads the AI Economist team at Salesforce Research, which works on deep reinforcement learning and AI simulations to design economic policy. His work has been widely covered in the media, including the Financial Times, Axios, Forbes, Zeit, Volkskrant, MIT Tech Review, and others. He holds a Ph.D. in Physics from Caltech (2018) and interned with Google Research and Google Brain. Before machine learning, he studied mathematics and theoretical physics at the University of Cambridge, Harvard University, and Utrecht University. He received the Dutch Lorenz graduation prize for his thesis on topological string theory and was twice awarded the Dutch national Huygens scholarship.