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'Where’s the I-O?' Artificial Intelligence and Machine Learning in Talent Management Systems

Authors :
Gonzalez, Manuel
Capman, John
Oswald, Frederick
Theys, Evan
Tomczak, David
Source :
Personnel Assessment and Decisions, Vol 5, Iss 3 (2019)
Publication Year :
2019
Publisher :
International Personnel Assessment Council (IPAC), 2019.

Abstract

Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption by organizations seeking to identify and hire high-quality job applicants. Yet the volume, variety, and velocity of professional involvement among I-O psychologists remains relatively limited when it comes to developing and evaluating AI/ML applications for talent assessment and selection. Furthermore, there is a paucity of empirical research that investigates the reliability, validity, and fairness of AI/ML tools in organizational contexts. To stimulate future involvement and research, we share our review and perspective on the current state of AI/ML in talent assessment as well as its benefits and potential pitfalls; and in addressing the issue of fairness, we present experimental evidence regarding the potential for AI/ML to evoke adverse reactions from job applicants during selection procedures. We close by emphasizing increased collaboration among I-O psychologists, computer scientists, legal scholars, and members of other professional disciplines in developing, implementing, and evaluating AI/ML applications in organizational contexts.

Details

Language :
English
ISSN :
23778822
Volume :
5
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Personnel Assessment and Decisions
Publication Type :
Academic Journal
Accession number :
edsdoj.fb5f46af9ef140ecbd8926a858ef2480
Document Type :
article
Full Text :
https://doi.org/10.25035/pad.2019.03.005