Brian Jabarian

Howard and Nancy Marks Fellow and Roman Family Center for Decision Research Principal Researcher Brian Jabarian

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Education

PhD, Economics, Paris School of Economics, 2023
PhD, Philosophy, Panthéon-Sorbonne University, 2023
MSc, Philosophy of Science, London School of Economics, 2017
BA, Philosophy and MA, Economics, Aix-Marseille University, 2013-2015

BACKGROUND & RESEARCH INTERESTS

Dr. Brian Jabarian is an economist studying how new technologies reshape cognitive work, decision-making, and the design of firms, markets, and institutions.

Partnering with industry and public organizations, he runs experiments to study (i) the causal effects of AI on productivity, behavior, and organization in global markets; (ii) the ethical, institutional, and welfare consequences of AI transformation; (iii) the role of AI in accelerating scientific knowledge and transparency.

He is the Howard and Nancy Marks Fellow and Roman Family Center for Decision Research Principal Researcher at the University of 黑料传送门 Booth Business School. He is an Affiliated Researcher with the Booth Center for Applied AI, an Invited Researcher at J-PAL, a Research Network Member, Innovation Growth Lab (IGL), a Research Affiliate at Joint Initiative Latin American Experimental Economics (JILAEE), and a Research Network Affiliate at the Center for Economic Studies + Ifo Institute (CESifo).

SELECTED PUBLICATIONS & PRESENTATIONS

  1. Jabarian, Brian*, and Luca Henkel, “Voice AI in Firms: A Natural Field Experiment on Automated Job Interviews”, Job Market Paper
  2. Charness, Gary, Brian Jabarian*, and John A. List. "The next generation of experimental research with LLMs." Nature Human Behaviour (2025): 1-3.
  3. Jabarian, Brian. "Large Language Models for Behavioral Economics: Internal Validity and Elicitation of Mental Models." arXiv preprint arXiv:2407.12032 (2024)., in preparation for Elgar Encyclopedia of Experimental Social Science
  4. Jabarian, Brian. "Large Language Models for Behavioral Economics: Synthetic Mental Models and Data Generalization." Available at SSRN 4880894 (2024).  in preparation for Elgar Encyclopedia of Experimental Social Science
  5. Jabarian, Brian. "Automated Cognitive Expertise and Human-AI Error Decomposition”
  6. Jabarian, Brian*, and Alex Imas, “Artificial Writing and Automated Detection”
  7. Matthew O. Jackson, Qiaozhu Mei, Stephanie W. Wang, Yutong Xie, Walter Yuan, Seth Benzell, Erik Brynjolfsson, Colin F. Camerer, James Evans, Brian Jabarian, Jon Kleinberg, Juanjuan Meng, Sendhil Mullainathan, Asu Ozdaglar, Thomas Pfeiffer, Moshe Tennenholtz, Robb Willer, Diyi Yang, and Teng Ye, “AI Behavioral Science”
  8. Jabarian, Brian, and Pëllumb Reshidi “Screening Labor with AI and Humans: Optimal Choice and Welfare” (Field Data Collection Completed)
  9. Jabarian, Brian, and Andrew Koh, “Human-AI Learning: Theory and Field Evidence from Job Interviews” (Field Data Collection Completed)
  10. Michael Cuna, Faith Fatchen, Brian Jabarian, Faisal Kattan, Min Sok Lee and John List “Critical Thinking and Economic Impacts: A Natural Field Experiment in Saudi Arabia on Educational and Labor Performance”  (Pilot Data Collection)


    *denotes lead author