JANUARY MEETING: Thursday, January 29, 2026 at 5:30pm (US Central)

NEW LOCATION:
ESAM Conference Room, Tech M416
2145 Sheridan Road, Evanston, IL 60208

AGENDA:
5:30pm - Meet and greet with refreshments
6:00pm - Talk with Moh Hosseinioun, PhD, Alfred Sloan Foundation Postdoctoral Fellow, Kellogg School of Management and Northwestern Institute on Complex Systems

TALK TITLE:
AI Reshapes the Practice of Science: Evidence from Two Decades of Research Proposals

ABSTRACT:
This project draws on a proprietary corpus of full-text and budgetary data from all (accepted and rejected) grant proposals submitted over the past two decades to a major research funding agency, offering a rare empirical lens for assessing the economic and scientific returns on investment (ROI) in Artificial Intelligence (AI). Using large language models (LLMs), we systematically classify proposals by AI engagement, distinguishing algorithmic types (e.g., simple nearest neighbor classifier vs. deep neural networks) and depth of integration (e.g., mentioning an algorithm as a benchmark vs. applying AI for inference). We link these classifications to highly granular budget data to examine how AI reshapes scientific production, reallocating funding across human capital costs, equipment and operational expenses, and overhead. Beyond resource allocation, we analyze project design, team size, duration, and applicant profiles, to study how AI alters the organization and execution of research. Leveraging both funded and unfunded proposals, we estimate the impact of AI use on proposal success, research output, and downstream career outcomes. This allows us to quantify not just the direct benefits of AI for scientific discovery, but also the opportunity costs and career implications for researchers adopting AI. Beyond offering unique insights into how AI reshapes the practice of science, our results contribute to emerging frameworks in the economics of science and innovation policy. In doing so, we offer practical insights into which types of AI investment yield sustained returns at the institutional and individual level, and where investments may be driven more by hype than value.

DATA SCIENCE NIGHTS are monthly meetings featuring presentations and discussions about data-driven science and complex systems, organized by Northwestern University graduate students and scholars. Students and researchers of all levels are welcome! For more information: http://bit.ly/nico-dsn

FUTURE DATES:
Data Science Nights will be held on Thursday evenings in the winter and spring terms, on February 26, March 19, April 30, and May 28, 2026.

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