Early-Stage Center Research: Fall/Winter Funded Projects

This year, thanks to our generous alumni, the Center began a program to fund competitive research projects from across Booth. These funds are designed to support novel, innovative work to help our researchers and faculty kickstart new projects and further our mission behind the thoughtful application of Artificial Intelligence. 

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Joshua Conrad Jackson, Assistant Professor of Behavioral Science at Chicago Booth, is assessing how different social media algorithms influence user behavior and political discourse during the U.S. election cycle. By randomly assigning machine-learning–created algorithms—including one with an intervention designed to reduce polarization—the study tracks shifts in political perceptions and online sentiment. This project harnesses AI to address real-world challenges in digital communication and democratic engagement, and it is made possible through the generous support of our alumni.

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Another project, led by Anders Humlum, Assistant Professor of Economics at Chicago Booth, utilizes alumni funds to conduct two surveys on AI chatbot adoption. One survey follows up on earlier work by examining changes in ChatGPT use across 11 occupations and expanding the analysis to include other chatbots and firm responses. The second survey tests whether offering a free month of ChatGPT Plus can spur sustained use among underrepresented groups, shedding light on how targeted interventions can promote equitable access to AI benefits in society and the workplace.

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Predoctoral student Janani Sekar worked alongside Assistant Professor of Marketing Giovanni Compiani on experimental research leveraging machine learning to analyze unstructured data—such as texts and images—from e-commerce pages. Compiani’s work mitigates biased price elasticity estimates by properly controlling for product differences and estimates product similarities to develop a reliable model for product elasticity. Sekar further validated the robustness of this approach by estimating the stability of these similarity measures over time. This innovative approach has notable implications for refining market analysis in real-world situations and exemplifies the impact of our predoctoral fellows’ contributions on tangible applications of AI.

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Kirill Skobelev, another one of our predoctoral fellows, worked with Chicago Booth Professor Killian Huber as he spearheaded a research project creating an AI pipeline that processes “earnings call” transcripts to extract a structured dataset capturing commodity price expectations. This work opens new avenues for leveraging unstructured financial data and further enhances the Center’s application of AI in market analysis.

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Skobelev has also been contributing his time to Alexander Todorov’s lab as they use AI to understand the idiosyncrasies of individual tastes. By exploring global shared perceptions and individual differences, Skobelev and Todorov have applied AI tools to the food domain, offering granular insights into consumer behavior and rapid decision-making.

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Many of these projects are in a conceptual stage and embody the kind of research done at the center as we highlight the potential of AI innovation in transforming industries, from finance to the food industry. These research approaches and their potential for change through innovation wouldn't be possible without the support of our alumni network.

Here at CAAI, we are committed to fostering groundbreaking AI research. Faculty, do you have an idea for AI innovation and its application? Apply for research funds to help you pursue interesting applications of AI. 

Thank you to our alumni, whose support makes stories like these possible. Stay tuned for updates as these projects evolve and new research emerges.