Frontiers in Machine Learning and Economics: Methods and Applications

The Frontiers in Machine Learning and Economics: Methods and Applications conference is a prominent event hosted by the Federal Reserve Bank of Philadelphia in collaboration with the Center for Applied Artificial Intelligence at the University of Chicago Booth School of Business. This annual conference aims to unite leading researchers who operate at the intersection of machine learning and social sciences.

It encourages the submission of papers that explore various pertinent topics, including methodological advancements in analyzing complex and high-dimensional data, innovations in natural language processing particularly related to causal inference, and the societal impacts of AI and algorithmic decision-making. Furthermore, the conference is open to submissions from disciplines outside of economics, provided they utilize methods and data that resonate with economists.

The conference will feature approximately ten selected papers, each assigned a discussant to enhance the dialogue surrounding their findings. The submissions are nonarchival, encouraging early-stage drafts to be presented and discussed. Interested participants are expected to submit their completed manuscripts in PDF format, clearly indicating the presenting author.

Esteemed professionals from the academic and economic sectors, including professors and senior economists, are involved, ensuring a high-caliber discussion and examination of the selected works. This collaborative environment is designed not only to showcase innovative research but also to foster interdisciplinary dialogue on the evolving methods and applications of machine learning in economics.