Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decision-making in the
- PDF / 602,788 Bytes
- 54 Pages / 439.37 x 666.142 pts Page_size
- 51 Downloads / 209 Views
Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decisionmaking in the context of HR recruitment and HR development Alina Ko¨chling1
•
Marius Claus Wehner1
Received: 15 October 2019 / Accepted: 1 November 2020 The Author(s) 2020
Abstract Algorithmic decision-making is becoming increasingly common as a new source of advice in HR recruitment and HR development. While firms implement algorithmic decision-making to save costs as well as increase efficiency and objectivity, algorithmic decision-making might also lead to the unfair treatment of certain groups of people, implicit discrimination, and perceived unfairness. Current knowledge about the threats of unfairness and (implicit) discrimination by algorithmic decision-making is mostly unexplored in the human resource management context. Our goal is to clarify the current state of research related to HR recruitment and HR development, identify research gaps, and provide crucial future research directions. Based on a systematic review of 36 journal articles from 2014 to 2020, we present some applications of algorithmic decision-making and evaluate the possible pitfalls in these two essential HR functions. In doing this, we inform researchers and practitioners, offer important theoretical and practical implications, and suggest fruitful avenues for future research. Keywords Fairness Discrimination Perceived fairness Ethics Algorithmic decision-making in HRM Literature review
1 Introduction Algorithmic decision-making in human resource management (HRM) is becoming increasingly common as a new source of information and advice, and it will gain more importance due to the rapid growth of digitalization in organizations. & Alina Ko¨chling [email protected] 1
Faculty of Business Administration and Economics, Heinrich-Heine-University Du¨sseldorf, Universita¨tsstrasse 1, 40225 Dusseldorf, Germany
123
Business Research
Algorithmic decision-making is defined as automated decision-making and remote control, as well as standardization of routinized workplace decisions (Mo¨hlmann and Zalmanson 2017). Algorithms, instead of humans, make decisions, and this has important individual and societal implications in organizational optimization (Chalfin et al. 2016; Lee 2018; Lindebaum et al. 2019). These changes in favor of algorithmic decision-making make it easier to discover hidden talented employees in organizations and review a large number of applications automatically (Silverman and Waller 2015; Carey and Smith 2016; Savage and Bales 2017). In a survey of 200 artificial intelligence (AI) specialists from German companies, 79% stated that AI is irreplaceable for competitive advantages (Deloitte 2020). Several commercial providers, such as Google, IBM, SAP, and Microsoft, already offer algorithmic platforms and systems that facilitate current human resource (HR) practices, such as hiring and performance measurements (Walker 2012). In turn, well-known and large companies, such as Vodafone, Intel, Unilever, and I
Data Loading...
