Ethics Guidelines for Using AI-based Algorithms in Recruiting: Learnings from a Systematic Literature Review

Abstract

To reduce the workload of employees working in Human Resource departments and to avoid bias in pre-selection of applicants, an increasing number of companies deploy Artificial Intelligence (AI)-based algorithms. Some examples such as Amazon's discriminating recruiting algorithm showed that algorithms are not free of unethical decision making. Although there already exists a variety of ethics principles for AI-based systems, those are usually hardly being applicable to specific use cases such as using AI-based algorithms in recruiting processes. To address this issue and to provide guidance for researchers and practitioners, we conducted a systematic literature review (keyword and backwards search) on existing ethics guidelines and principles for AI and extracted aspects that seemed applicable to guide recruiting processed. Based on 28 relevant papers we derived actionable guidelines for using AIbased algorithms in recruiting processes. We categorized our guidelines into the aspects of fairness, avoidance of discrimination and avoidance of bias.

Applying XAI to an AI-based system for candidate management to mitigate bias and discrimination in hiring

“…Furthermore, we used several questionnaires to assess different factors that might have influenced the results (Table 2). We used these controlling variables, as previous research has suggested considering a related combination in similar study contexts (Hofeditz et al, 2022a(Hofeditz et al, , 2022bMirbabaie et al, 2021aMirbabaie et al, , 2021bMirbabaie et al, , 2022.…”

“…A lack of documentation often implies that discrimination cannot be proven (Sabeg & Me´haignerie, 2006), and thus, decision makers do not face negative consequences for unethical behavior. To mitigate unethical human behavior, previous research has suggested applying AI-based systems in hiring (Hofeditz et al, 2022a(Hofeditz et al, , 2022bSühr et al, 2021), as AI is already being used by some organizations to perform the preselection of applicants (Laurim et al, 2021). However, in practice, these systems are not in charge of making the final decision (without a human decision maker).…”

Persistence, Emergence, and Fadeout: Influence of AI Teammates on the Salience of Human Identities at Work

“…To process the candidates' data, the use of artificial intelligence (AI)-based algorithms has become an established tool for an increasing number of organizations (Black & van Esch, 2020;Fernández-Martínez & Fernández, 2020;Marks, 2022;Mayer, Anne-Sophie;Strich, Franz;and Fiedler, 2020). The use of AI-based algorithms can reduce the workload of the employees that are involved in the recruiting process (Hofeditz et al, 2022). For example, an AI can screen résumés and examine data of applicants to reduce the amount of data for manual review (Marks, 2022;Raghavan et al, 2019).…”