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Past as prologue: Taylorism, the new scientific management and managing human capital

Dee Birnbaum (Department of Commerce and Business, Rhodes College, Memphis, Tennessee, USA)
Mark Somers (Martin Tuchman School of Management, New Jersey Institute of Technology, Newark, New Jersey, USA)

International Journal of Organizational Analysis

ISSN: 1934-8835

Article publication date: 5 May 2022

Issue publication date: 7 November 2023

2333

Abstract

Purpose

The purpose of this paper is to explore parallels between scientific management and the new scientific management to gain insight into applications of machine learning and artificial intelligence (AI) to human resource management and employee assessment.

Design/methodology/approach

Analysis of Taylor’s work and its interpretation by scholars is contrasted with modern analysis of human resource analytics to demonstrate conceptual and methodological commonalities between the old and the new forms of scientific management.

Findings

The analysis demonstrates how the epistemology, ethos and cultural trajectory of scientific management has resulted in a mindset that has influenced the implementation and objectives of the new scientific management with respect to human resources analytics.

Social implications

This paper offers an alternative to the view that machine learning and AI as applied to work and employees are beneficial and points out why important challenges have been overlooked and how they can be addressed.

Originality/value

Commonalties between Taylorism and the new scientific management have been overlooked so that attempts to gain an understanding of how machine learning is likely to influence work, employees and work organizations are incomplete. This paper provides a new perspective that can be used to address challenges associated with applications of machine learning to work design and employee rights.

Keywords

Citation

Birnbaum, D. and Somers, M. (2023), "Past as prologue: Taylorism, the new scientific management and managing human capital", International Journal of Organizational Analysis, Vol. 31 No. 6, pp. 2610-2622. https://doi.org/10.1108/IJOA-01-2022-3106

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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