Management by Algorithm? Human Capital in the Age of Intelligent Machines

30 Pages Posted: 8 Jul 2021

See all articles by Eirik Sjåholm Knudsen

Eirik Sjåholm Knudsen

Norwegian School of Economics (NHH) - Department of Strategy and Management

Lasse B. Lien

Norwegian School of Economics (NHH)

Robert Wuebker

University of Utah - David Eccles School of Business

Date Written: July 2, 2021

Abstract

This paper explores machine allocation of human resources to teams and tasks within organizations, and its implications for the management of human capital. We consider a thought experiment where all firms have access to the same basic machine learning technology, and show that the ability of firms to create advantages from human capital differs due to variation in the size of a firm’s internal labor market, employee data disclosure, and characteristics of a firm’s task structure and the dynamism of its competitive environment. Our analysis leads to novel and counter-intuitive predictions about the potential role of machines in the management of human capital with potentially wide-reaching implications for research, practice and policy. More broadly, we contribute to active conversations about the future impact of machine intelligence on firm strategy and human capital management.

Keywords: Human Capital, Artificial Intelligence, Internal Labor Markets, Data Disclosure

Suggested Citation

Knudsen, Eirik Sjåholm and Lien, Lasse B. and Wuebker, Robert, Management by Algorithm? Human Capital in the Age of Intelligent Machines (July 2, 2021). Available at SSRN: https://ssrn.com/abstract=3878909 or http://dx.doi.org/10.2139/ssrn.3878909

Eirik Sjåholm Knudsen

Norwegian School of Economics (NHH) - Department of Strategy and Management ( email )

Breiviksveien 40
N-5045 Bergen
Norway

Lasse B. Lien

Norwegian School of Economics (NHH) ( email )

Helleveien 30
Bergen, 5045
Norway
+47 55959726 (Phone)

Robert Wuebker (Contact Author)

University of Utah - David Eccles School of Business ( email )

1645 East Campus Circle Drive
Salt Lake City, UT 84112-9304
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
28
Abstract Views
143
PlumX Metrics