Working Papers
Artificial Writing and Automated Detection New Paper
with Alex Imas
🌐 SSRN version
AI Behavioral Science New Paper
with Matthew O. Jackson, Qiaozhu Mei, Stephanie W. Wang, Yutong Xie, Walter Yuan, Seth Benzell, Erik Brynjolfsson, Colin F. Camerer, James Evans, Jon Kleinberg, Juanjuan Meng, Sendhil Mullainathan, Asu Ozdaglar, Thomas Pfeiffer, Moshe Tennenholtz, Robb Willer, Diyi Yang, and Teng Ye
🌐 SSRN version
The Virtues of Lab Experiments
with Gary Charness, James Cox, Charles Holt, Catherine Eckel
🌐 CESifo version
R&R at Journal of Economic Behavior and Organization
Distributional Approach to Risk Preferences
with Nir Chemaya, Charles Johnson, Enoch Yeung, Gary Charness
🌐 Pre-print version
Two-Ball Ellsberg Paradox
with Simon Lazarus
🌐 CESifo version
Critical Thinking and Storytelling Contexts
with Elia Sartori
🌐 CESifo version
Selected Work in Progress
Automated Cognitive Expertise and Human-AI Error Decomposition Coming Soon
Screening Labor with AI and Humans: Optimal Choice and Welfare Field Data Collected
with Pëllumb Reshidi
Human-AI Learning: Theory and Field Evidence from Job Interviews Field Data Collected
with Andrew Koh
Critical Thinking and Economic Impacts: A Natural Field Experiment in Saudi Arabia on Educational and Labor Performance Pilot Data Collected
with Michael Cuna, Faith Fatchen, Faisal Kattan, Min Sok Lee and John List
Publications
Peer-Reviewed Articles
The Next Generation of Experimental Research with LLMs
with Gary Charness and John List
🌐 NBER No. 31679
Nature Human Behaviour, 2025
Covered in the World Economic Forum, Chicago Booth Review, VoxEU Column
Invited Survey and Book Chapters
LLMs for Behavioral Economics: Ensuring Internal Validity and Elicitating Mental Models
Invited Entry under preparation for the Elgar Encyclopedia of Experimental Social Science
🌐 SSRN version
LLMs for Behavioral Economics: Synthetic Mental Models and Data Generalization
Invited Entry under preparation for the Elgar Encyclopedia of Experimental Social Science
🌐 SSRN version
Black Boxes: Mental Models and AI Models
Invited Chapter under preparation for the Oxford Research Encyclopedia of Economics and Finance
🌐 SSRN version
Doctoral Theses
PhD Thesis in Economics, Paris School of Economics, 2023
Online Manuscript: [pre-print]
Citation APA: Jabarian, B. (2023). The Economics of Moral Uncertainty: Essays in Behavioral and Experimental Economics (Doctoral dissertation, Université Panthéon-Sorbonne-Paris I).
Title: The Economics of Moral Uncertainty
Committee: Jean-Marc Tallon (Supervisor), Roland Bénabou (Chair), Leeat Yariv, Mohammed Abdelaoui, Nicolas Jacquemet
Abstract: This thesis, rooted in experimental economics, political behavioral economics, and macroeconomic behavioral economics, tackles diverse topics concerning the decision-making processes of economic agents. In the first chapter, we conduct an incentivized experiment on a nationally representative US sample (N=708) to test whether people prefer to avoid ambiguity even when it means choosing dominated options. In contrast to the literature, we find that 55% of subjects prefer a risky act to an ambiguous act that always provides a larger probability of winning. Our experimental design shows that such a preference is not mainly due to a lack of understanding. We conclude that subjects avoid ambiguity per se rather than avoiding ambiguity because it may yield a worse outcome. Such behavior cannot be reconciled with existing models of ambiguity aversion straightforwardly. In the second chapter, in an incentivized online social media experiment (N = 706), we show that different digital storytelling formats – different visual designs and writing styles to present the same set of facts – affect the intensity at which individuals become critical thinkers. Intermediate-length designs (Facebook posts) are most effective at triggering individuals into critical thinking. Individuals with a high need for cognition mostly drive the differential effects of the treatments. We further explore the implications of such results for the welfare and political economy. Particularly, we establish that increasing the share of critical thinkers – individuals who are aware of the ambivalent nature of a certain issue – in the population increases the efficiency of surveys (elections) but might increase surveys’ bias. In the third chapter, we present a novel climate-macroeconomic model, Nested Inequalities Climate-Economy with Risk, and Inequality Uncertainty (NICERIU). We also introduce a social welfare function, the Worldview-Inclusive Welfare. This latter incorporates heterogeneous worldviews regarding welfare and uncertainty about inequality, proposing redistributive economic policies based on equality-distributed equivalence and a novel axiom of minimal comparability of worldviews. NICERIU has been calibrated using a representative sample from the US population (N=500), and the calibration outcomes reveal intriguing insights. With symmetrically weighted distinct world-views, the optimal taxation policy closely approximates conservatively the taxation policy based on a particular worldview but differs in specific ways. In summary, this thesis explores various often overlooked aspects within traditional approaches to economics. It challenges models of ambiguity aversion, highlights the impact of narrative formats on critical thinking, and proposes a climate-economic model that incorporates uncertainty about inequality. The obtained results call for profound reflection and underscore the importance of integrating diverse aspects of decision-making processes into economic analyses.
PhD Thesis in Philosophy, Department of Philosophy, University Panthéon-Sorbonne Paris 1, 2023
Online Manuscript: [pre-print]
Citation APA: Jabarian, B. (2023). Operationalizing moral uncertainty: a framework for critical thinking in an uncertain world (Doctoral dissertation, Université Panthéon-Sorbonne-Paris I).
Title: Operationalizing Moral Uncertainty
Committee: Laurent Jaffro (primary supervisor), Franz Dietrich (co-supervisor), Marc Fleurbaey (Chair), Pierre Livet, Richard Bradley, Katie Steele
Abstract: This Ph.D. in philosophy explores the normative uncertainty problem, i.e., the complex ethical problem of what we should do when uncertain about what we should do. We conduct our thesis in the tradition of the long-forgotten philosophy of science of operationalization. The latter is a thorough analytical approach that allows for applied investigations of a concept whose empirical implications are neither proven nor clear. In the case of an ethical evaluation or choice problem, operationalization includes two main dimensions: (1) providing a framework for reasoning, comparing the values of options, and decision-making by individuals or groups; (2) providing empirical evidence to demonstrate the concept’s relevance for applied research and further scientific investigations. We divide our thesis into two main parts based on these dimensions. A preceding introduction addresses normative uncertainty and its relations to other ethical and meta-ethical concepts. Part I provides a comprehensive framework for comparing the values of options, reasoning, and making individual decisions under normative uncertainty, depending on the types and amount of information available to the decision-maker. Part II demonstrates how we may employ the humanities in survey methods and establish normative uncertainty as an empirical fact by combining both disciplines. The conclusion summarizes our thesis’s main contributions.