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on Sociology of Economics |
| By: | Joshua S. Gans |
| Abstract: | This paper examines a new moral hazard in delegated decision-making: authors can embed hidden instructions—known as prompt injections—to bias AI referees in academic peer review, thereby hijacking machine recommendations. Because AI reviews are relatively inexpensive compared to manual assessments, referees would otherwise delegate fully, which undermines quality. The paper shows that moderate detection of manipulation can paradoxically improve welfare. With intermediate detection probabilities, only low-quality authors undertake manipulation, and detection becomes informative about quality, inducing referees to mix between manual and AI reviews. This partially separating equilibrium preserves the value of peer review when AI quality is intermediate. When detection is too low, all bad papers are manipulated and the market unravels; when detection is perfect, referees use only AI and acceptance collapses. Thus, some prompt injection must be tolerated to sustain the market: it disciplines referees and generates information. The results caution against zero-tolerance enforcement and highlight how prompt injection can, counterintuitively, play a welfare-enhancing role when AI reviews are easily produced. |
| JEL: | D82 D86 O33 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34082 |
| By: | Atsushi INOUE; Ryuichi TANAKA |
| Abstract: | Currently, the proportion of female students in economics and business faculties at four-year universities in Japan remains at about 30%. This paper analyzes the determinants of the gender gap in choice of majors, focusing on enrollment in economics and business programs at four-year universities in Japan. Given the strong emphasis on mathematical skills required in these disciplines, they may be regarded as “science-oriented†fields within the broader category of humanities and social sciences. This study investigates whether the underrepresentation of women in economics and business programs shares structural similarities with the gender imbalance observed in STEM majors. Using data from the Longitudinal Survey of Newborns in the 21st Century (2001 cohort), we compare the determinants of choosing a STEM major to those of choosing an economics or business major among university entrants. Results indicate that a common positive determinant for both STEM and economics/business major selection is proficiency in mathematics during the first year of high school, while proficiency in the Japanese language is negatively associated with choosing these majors. However, clear differences emerge in terms of career aspirations: having clear occupational aspirations in the first year of high school is positively correlated with STEM major selection but negatively correlated with economics/business major selection. Further, using the Blinder–Oaxaca decomposition method to analyze determinants of gender gaps, we find that 49% of the gender gap in STEM enrollment can be explained by observable characteristics, such as subject aptitude. In contrast, only 14% of the gender gap among humanities students choosing economics/business majors can be attributed to such observable factors. These findings suggest that the majority of the gender gap in economics and business major selection is driven by factors other than observable attributes. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:eti:rdpsjp:25018 |