IDLab Researchers Win Russian Science Foundation Grants
Two research projects from the HSE University Perm have been awarded grants by the Russian Science Foundation (RSF). The projects were selected as part of the RSF’s competitive funding program for fundamental and exploratory research carried out by individual scientific groups. Out of nearly 4,500 proposals, 534 were selected based on expert review—including two from the International Laboratory of Intangible-driven Economy at HSE University
Project: “Comparative Analysis of Decision-Making by AI Agents and Humans in Economic Contexts”
This project explores how artificial intelligence agents compare to real people when making economic decisions. The research team will investigate whether modern language models—such as ChatGPT—can accurately mimic human behavior in classic economic scenarios, like trust or cooperation games.
The goal is to assess whether AI can serve as a substitute or a complement to human participants in behavioral economics experiments. This approach could not only advance theoretical understanding but also reduce the costs of empirical research. The findings are expected to be applicable in economic modeling, forecasting, risk management, and policy development.
The project team includes researchers from both HSE University from Perm, and Moscow, ranging from experienced scientists to early-career researchers and students. The project is led by Petr Parshakov, Head of the International Laboratory of Intangible-driven Economy at HSE University, Perm and Professor at the Department of Economics and Finance. The research will take place over a three-year period, from 2025 to 2027.
Project: “Burnout Syndrome: AI-Based Diagnostics and Economic Impact Assessment”
This project aims to generate new empirical insights into the causes and economic consequences of professional burnout using artificial intelligence. AI—particularly natural language processing (NLP) techniques—offers an objective way to assess burnout that avoids common biases like social desirability, and can be used to analyze large-scale data samples.
The project focuses on three key objectives:
- Conduct a comprehensive review of burnout syndrome, its economic implications, and measurement approaches, with an emphasis on AI-based methods.
- Develop a diagnostic framework for identifying burnout using AI, especially NLP tools.
- Empirically identify the key factors and economic effects associated with burnout.
A central outcome of the project will be a methodological framework for measuring burnout syndrome and a practical algorithm for its application. The team will also develop a new metric to assess individual susceptibility to burnout through analysis of Russian-language textual communication. Using publicly available data, researchers will test hypotheses on how factors like age, gender, and external shocks contribute to burnout, as well as the impact of burnout on individual productivity.
Unlike previous studies, the use of this novel burnout metric will allow for significantly broader samples and, for the first time, yield objective empirical assessments of burnout that are not distorted by behavioral biases.
The project is being carried out by researchers from the International Laboratory of Intangible-driven Economy. It is led by Marina Zavertyaeva, Senior Research Fellow at the Laboratory and Professor at the Department of Economics and Finance.