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The Gatekeeper Effect: The Implications of Pre-Screening, Self-Selection, and Bias for Hiring Processes

选择(遗传算法) 选择偏差 经济 计量经济学 心理学 计算机科学 统计 数学 人工智能
作者
Moran Koren
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
标识
DOI:10.1287/mnsc.2021.03918
摘要

We study the problem of screening in decision-making processes under uncertainty, while focusing on the impact of adding an additional screening stage, commonly known as a “gatekeeper.” Although our main analysis is rooted in the context of job market hiring, the principles and findings are broadly applicable to areas such as educational admissions, patient healthcare selection, and financial loan approvals. The gatekeeper’s role is to assess applicant suitability before significant costs are incurred. Our study reveals that although gatekeepers are designed to streamline selection processes by filtering out the candidates who are less likely to be selected, sometimes they inadvertently affect the candidate’s own decision-making process. We explore the conditions under which the introduction of a gatekeeper can enhance or impede the efficiency of these processes. Additionally, we consider how gatekeeping strategies can be adapted to influence the accuracy of selection decisions. Our research also extends to scenarios in which gatekeeping is influenced by historical biases, particularly in competitive settings like hiring. We discover that candidates confronted with a statistically biased gatekeeping process are more likely to withdraw from the job application process, thereby perpetuating the previously mentioned historical biases. The study suggests that measures such as affirmative action can effectively address these biases. Although centered on hiring, the insights and methodologies from our study have significant implications for a wide range of fields to which screening and gatekeeping are integral. This paper has been This paper was accepted by Nicolas Stier-Moses for the Special Issue on the Human-Algorithm Connection. Funding: Financial support from the Center of Mathematical Sciences and Applications (CMSA) at Harvard University and the Ministry of Science and Technology of Israel (Yitzhak Shamir Fellowship) is gratefully acknowledged.

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