My Boss the Computer: A Bayesian analysis of socio-demographic and cross-cultural determinants of attitude toward the Non-Human Resource Management

58 Pages Posted: 13 Mar 2021

See all articles by Peter Mantello

Peter Mantello

affiliation not provided to SSRN

Tung Ho

Vietnam Academy of Social Sciences - Institute of Philosophy; Ritsumeikan Asia Pacific University, Students

Minh-Hoang Nguyen

Centre for Interdisciplinary Social Research, Phenikaa University

Quan Hoang Vuong

Université Libre de Bruxelles (ULB) - Solvay Brussels School of Economics and Management; Phenikaa University

Date Written: January 21, 2021

Abstract

Human resource management technologies have moved from biometric surveillance to emotional artificial intelligence (AI) that monitor employees’ engagement and productivity, analyze video interviews and CVs of job applicants. The rise of the US$20 billion emotional AI industry will transform the future workplace. Yet, besides no international consensus on the principles or standards for such technologies, there is a lack of cross-cultural research on future job seekers’ attitude toward such use of AI technologies. This study collects a cross-sectional dataset of 1,015 survey responses of international students from 48 countries and 8 regions worldwide. A majority of the respondents (52%) are concerned about being managed by AI. Following the hypothetico-deductivist philosophy of science, we use the MCMC Hamiltonian approach and conduct a detailed comparison of 10 Bayesian network models with the PSIS-LOO method. We consistently find having a higher income, being male, majoring in business, and/or self-rated familiarity with AI correlate with a more positive view of emotional AI in the workplace. There is also a stark cross-cultural and cross-regional difference. Our analysis shows people from economically less developed regions (Africa, Oceania, Central Asia) tend to exhibit less concern for AI managers. And for East Asian countries, 64% of the Japanese, 56% of the South Korean, and 42% of the Chinese professed the trusting attitude. In contrast, an overwhelming majority of 75% of the European and Northern American possesses the worrying/neutral attitude toward being managed by AI. Regarding religion, Muslim students correlate with the most concern toward emotional AI in the workplace (β_Islam_Attitude’s mean =-0.16, sd =0.10; β_Buddhism_Attitude’s mean =-0.05, sd =0.07; β_Christian_Attitude ‘s mean = -0.10, sd= 0.09). When religiosity is higher, the correlation becomes stronger for Muslim and Buddhist students. This paper adds a cross-cultural perspective to the literature, which is currently skewed toward country-specific and profession-specific samples.

Keywords: Artificial Intelligence, AI Manager, Cross-Cultural Perception, Emotional AI, Emotional Surveillance, Non-Human Resource Management, Workplace Surveillance

JEL Classification: L82, C31, C63, O31

Suggested Citation

Mantello, Peter and Ho, Tung and Nguyen, Minh-Hoang and Vuong, Quan Hoang, My Boss the Computer: A Bayesian analysis of socio-demographic and cross-cultural determinants of attitude toward the Non-Human Resource Management (January 21, 2021). Available at SSRN: https://ssrn.com/abstract=3772076 or http://dx.doi.org/10.2139/ssrn.3772076

Peter Mantello

affiliation not provided to SSRN

Tung Ho (Contact Author)

Vietnam Academy of Social Sciences - Institute of Philosophy ( email )

1 Lieu Glai
Ba Dinh
Hanoi
Vietnam

Ritsumeikan Asia Pacific University, Students ( email )

Beppu
Japan

Minh-Hoang Nguyen

Centre for Interdisciplinary Social Research, Phenikaa University ( email )

Hanoi
Vietnam

Quan Hoang Vuong

Université Libre de Bruxelles (ULB) - Solvay Brussels School of Economics and Management ( email )

ULB CP 145/01
21 Ave. F.D. Roosevelt
Brussels, Bruxelles 1050
Belgium
+32-2-6504864 (Phone)
+32-2-6504188 (Fax)

HOME PAGE: http://www.ceb-ulb.com/vuong-quan-hoang.html

Phenikaa University ( email )

To Huu road, Yen Nghia
Ha Dong district
Hanoi, Hanoi 100803
Vietnam

HOME PAGE: http://sites.google.com/site/vuongqh2019/

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