
Machine Learning in Economics Summer Institute
MLESI introduces new methods and to build intuitions about how these methods can open up new questions for researchers.
Machine Learning in Economics Summer InstituteThursday, September 25
How is artificial intelligence (AI) going to change social science and how is social science going to change how AI is used? This conference will bring together researchers using AI to address issues in social science, including, but not limited to using AI to enable the use of new types of data in social science applications (e.g., text or images), using algorithms to solve problems or enhance decision-making in different economically relevant applications (e.g., hiring, lending, medicine, education, criminal justice), understanding how to help humans use algorithmic decision-aids as effectively as possible, or different approaches to designing and deploying these tools fairly and ethically. This cross-disciplinary conference aims to facilitate dialogue and generate insights into innovative methodologies, novel datasets, and emerging technologies that can reshape our understanding of the world and push the boundaries of knowledge across disciplines and fields, including experts from economics, sociology, law, behavioral sciences, artificial intelligence, and more.
All interested researchers are welcome to submit papers by May 1, 2025, through .
If you have any questions, please contact bfi-events@uchicago.edu.
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As a Principal Researcher at the Center for Applied AI, you conduct groundbreaking research exploring the intersection of AI with business disciplines, both independently and alongside Booth Faculty colleagues. Your work combines technical innovation with novel applications, generating significant contributions that advance understanding of AI's impact on business and society. You actively participate in the academic community through workshops and seminars, while also sharing your technical expertise by teaching quarterly workshops for fellow researchers.
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Pre-doctoral fellowships are an opportunity to work directly with faculty and experience research projects first hand for two years, before applying for a PhD. Our pre-doctoral fellows design and implement entire research pipelines, from data processing, to model development and evaluation, to summarizing and presenting results. In addition, fellows are able to connect with visiting experts and external collaborators, attend interactive seminars with University faculty, and participate in joint lab meetings, collaborating with and learning from other research teams.
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