Artificial Intelligence in Human Resources Management: Challenges and a Path Forward

doi:10.1177/0008125619867910

Paper

Artificial Intelligence in Human Resources Management: Challenges and a Path Forward

Published Apr 8, 2019 · Prasanna Tambe, P. Cappelli, V. Yakubovich

California Management Review

Q1 SJR score

597

Citations

33

Influential Citations

Full textSemantic Scholar

Abstract

There is a substantial gap between the promise and reality of artificial intelligence in human resource (HR) management. This article identifies four challenges in using data science techniques for HR tasks: complexity of HR phenomena, constraints imposed by small data sets, accountability questions associated with fairness and other ethical and legal constraints, and possible adverse employee reactions to management decisions via data-based algorithms. It then proposes practical responses to these challenges based on three overlapping principles—causal reasoning, randomization and experiments, and employee contribution—that would be both economically efficient and socially appropriate for using data science in the management of employees.

Highly Cited

Study Snapshot

Artificial intelligence in human resource management faces challenges like complexity, small data sets, accountability, and employee reactions, but can be overcome through causal reasoning, randomization, and employee contributions.

PopulationOlder adults (50-71 years)

Sample size24

MethodsObservational

OutcomesBody Mass Index projections

ResultsSocial networks mitigate obesity in older groups.

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Artificial Intelligence in Human Resources Management: Challenges and a Path Forward

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Citations

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