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.
Gonzalez, Manuel F.; Capman, John F.; Oswald, Frederick L.; Theys, Evan R.; and Tomczak, David L.
"“Where’s the I-O?” Artificial Intelligence and Machine Learning in Talent Management Systems,"
Personnel Assessment and Decisions: Number 5
, Article 5.
Available at: https://scholarworks.bgsu.edu/pad/vol5/iss3/5
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