paper-with-me

홈 › Papers

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

2023-12-28 · Moran Koren

We study the problem of screening in decision-making processes under uncertainty, focusing on the impact of adding an additional screening stage, commonly known as a 'gatekeeper.' While our primary analysis is rooted in the context of job market hiring, the principles and findings are broadly applicable to areas such as educational admissions, healthcare patient selection, and financial loan approvals. The gatekeeper's role is to assess applicants' suitability before significant investments are made. Our study reveals that while gatekeepers are designed to streamline the selection process by filtering out less likely candidates, they can sometimes inadvertently affect the candidates' 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 adjusting gatekeeping strategies might impact the accuracy of selection decisions. Our research also extends to scenarios where 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 applying, thereby perpetuating the previously mentioned historical biases. The study suggests that measures such as affirmative action can be effective in addressing these biases. While centered on hiring, the insights and methodologies from our study have significant implications for a wide range of fields where screening and gatekeeping are integral.

📄 PDF Abstract BibTeX arXiv:2312.17167

Code (0)

등록된 구현이 없습니다.

Tasks

Decision Making

Similar Papers 제목 키워드 기반

GateKeeper-GPU: Fast and Accurate Pre-Alignment Filtering in Short Read Mapping

2021-03-27 · Zülal Bingöl, Mohammed Alser, Onur Mutlu, Ozcan Ozturk 외

At the last step of short read mapping, the candidate locations of the reads on the reference genome are verified to compute their differences from the corresponding reference segments using sequence alignment algorithms…

GPU

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

2024-07-29 · Kyra Wilson, Aylin Caliskan

Artificial intelligence (AI) hiring tools have revolutionized resume screening, and large language models (LLMs) have the potential to do the same. However, given the biases which are embedded within LLMs, it is unclear …

FairnessLanguage ModelingLanguage ModellingRetrieval

GateKeeper: A New Hardware Architecture for Accelerating Pre-Alignment in DNA Short Read Mapping

2016-04-06 · Mohammed Alser, Hasan Hassan, Hongyi Xin, Oğuz Ergin 외

Motivation: High throughput DNA sequencing (HTS) technologies generate an excessive number of small DNA segments -- called short reads -- that cause significant computational burden. To analyze the entire genome, each of…

False Discovery Rate Control for Gaussian Graphical Models via Neighborhood Screening

2024-01-18 · Taulant Koka, Jasin Machkour, Michael Muma

Gaussian graphical models emerge in a wide range of fields. They model the statistical relationships between variables as a graph, where an edge between two variables indicates conditional dependence. Unfortunately, well…

Graph LearningVariable Selection

Pre-screening breast cancer with machine learning and deep learning

2023-02-05 · Rolando Gonzales Martinez, Daan-Max van Dongen

We suggest that deep learning can be used for pre-screening cancer by analyzing demographic and anthropometric information of patients, as well as biological markers obtained from routine blood samples and relative risks…

Deep Learningfeature selection