Designing gender-balanced evaluation committees with AI

J. Ignacio Conde-Ruiz, Miguel Díaz Salazar and Juan José Ganuza ()
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Juan José Ganuza: https://www.upf.edu/web/econ/faculty/-/asset_publisher/6aWmmXf28uXT/persona/id/3418872

Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra

Abstract: This paper combines artificial intelligence with economic modeling to design evaluation committees that are both efficient and fair in the presence of gender differences in economic research orientation. We develop a dynamic framework in which research evaluation depends on the thematic similarity between evaluators and researchers. The model shows that while topic balanced committees maximize welfare, this researchneutral-gender allocation is dynamically unstable, leading to the persistent dominance of the group initially overrepresented in evaluation committees. Guided by these predictions, we employ unsupervised machine learning to extract research profiles for male and female researchers from articles published in leading economics journals between 2000 and 2025. We characterize optimal balanced committees within this multidimensional latent topic space and introduce the Gender-Topic Alignment Index (GTAI) to measure the alignment between committee expertise and female-prevalent research areas. Our simulations demonstrate that AI-based committee designs closely approximate the welfare-maximizing benchmark. In contrast, traditional headcount-based quotas often fail to achieve balance and may even disadvantage the groups they intend to support. We conclude that AI-based tools can significantly optimize institutional design for editorial boards, tenure committees, and grant panels.

Keywords: machine learning; artificial intelligence; Topic Modeling; evaluation committees; committee quotas; research orientation (search for similar items in EconPapers)
JEL-codes: D72 D82 J16 J78 (search for similar items in EconPapers)
Date: 2026-01
New Economics Papers: this item is included in nep-sog
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