The Initial Screening Order Problem
CoRR(2023)
摘要
We investigate the role of the initial screening order (ISO) in candidate
screening processes, such as hiring and academic admissions. ISO refers to the
order in which the screener sorts the candidate pool before the evaluation. It
has been largely overlooked in the literature, despite its potential impact on
the optimality and fairness of the chosen set, especially under a human
screener. We define two problem formulations: best-k, where the screener
chooses the k best candidates, and good-k, where the screener chooses the
first k good-enough candidates. To study the impact of ISO, we introduce a
human-like screener and compare to its algorithmic counterpart. The human-like
screener is conceived to be inconsistent over time due to fatigue. Our analysis
shows that the ISO under a human-like screener hinders individual fairness
despite meeting group level fairness. This is due to the position bias, where a
candidate's evaluation is affected by its position within ISO. We report
extensive simulated experiments exploring the parameters of the problem
formulations both for algorithmic and human-like screeners. This work is
motivated by a real world candidate screening problem studied in collaboration
with a large European company.
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关键词
initial screening,order
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