Gender Bias in AI Recruitment Systems: A Sociological-and Data Science-based Case Study-Reference-Cited by-同舟云学术

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Gender Bias in AI Recruitment Systems: A Sociological-and Data Science-based Case Study

Published:2022-11-10 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Symposium on Technology and Society (ISTAS)
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Author:

Njoto Sheilla¹,Cheong Marc²,Lederman Reeva³,McLoughney Aidan³,Ruppanner Leah¹,Wirth Anthony³

Affiliation:

1. University of Melbourne,Faculty of Arts,Parkville,VIC,Australia

2. University of Melbourne,School of Computing and Information Systems & CAIDE,Parkville,VIC,Australia

3. University of Melbourne,School of Computing and Information Systems,Parkville,VIC,Australia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10226637/10227072/10227106.pdf?arnumber=10227106

Reference56 articles.

1. Historical comparison of gender inequality in scientific careers across countries and disciplines

2. Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring;sühr;arXiv [cs LG],2020

3. Gender Discrimination in Hiring: Evidence from a Cross-National Harmonized Field Experiment

4. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

5. Bias in Bios

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Steering Women out of Engineering: Career Assessment Tools as a Technology of Self‐Expressive Segregation;Sociological Inquiry;2024-05-17

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