HRM and AI: An HR-Centered Approach to Employers, Employees, and the Use of AI at Work

Abstract

Artificial intelligence (AI) is transforming the workplace for both employers and their employees. This transformation has brought some positives in terms of reliability and efficiency for work performance, customizability of job rewards, and enhancement of worker experiences (Glikson & Woolley, 2020). However, there have also been negative downsides ranging from job loss, amplified biases, and widening social inequality (Varma et al., 2023). Owing to its impact on jobs, the workplace, and the employment experience, it is incumbent that knowledge and understanding are up to date on how and why AI is influencing the design and practice of human resource management (HRM). Due to the nature of the topic, research on AI in HRM has tended to be very interdisciplinary, from incorporating technological fields when focused on the AI-based tools used in HR (e.g., Hickman et al., 2022), to the social sciences largely dealing with AI implementation and its consequences (e.g., Charlwood & Guenole, 2022; Hunkenschroer & Luetge, 2022). These different approaches to studying AI have thus resulted in a scattered body of understanding of AI in HRM, which in turn has raised concerns about the overall theoretical and methodological rigor of the discipline. For a field still in its infancy, scholars and practitioners would stand to gain from a more systematic approach aimed at demonstrating the benefits of studying AI specifically through a HR lens. Our current symposium contributes towards this need by featuring a collection of studies calling attention to two themes underlining a HR-driven approach to AI inquiry (Pan & Froese, 2023). The first theme centers around employees and how their experiences with HR at work are being influenced by AI. This incorporates research focusing on how AI-based selection interviews influence the job candidates’ reactions. Questions addressed include: What are the hidden costs of AI interviews for extroverted applicants? How do candidates’ emotions help explain why certain candidates perform better in AI interviews.? Extending beyond hiring to performance management, we also feature research investigating the effects of AI-driven feedback on employee perceptions of warmth and competence towards the source of the feedback, and how these perceptions drive feedback seeking behavior (Harris-Watson et al., 2023; Luo et al., 2023). The second theme deals with employers and the impact of AI on the practice of HR in organizations. Research under this theme describes the AI-driven influence on key traditional HR functions and responsibilities, including hiring-based recruitment and selection, performance management and feedback, and compensation-related pay information disclosure. Research investigating these phenomena ask how HR systems and professionals react and adapt to AI in their work (Basu et al., 2023). In so doing, key individual and organizational outcomes of AI-assisted HR are discussed (Malik et al., 2023). Our six presentations aim to address these issues and questions by providing evidence from varied rigorous methodological approaches. In so doing, this symposium will help to set the course for future research on AI in HR by highlighting overlooked phenomena and presenting evidence from novel contexts. Specifically, the symposium highlights the significant potential to advance the field by building theories grounded in novel and relevant HR-specific phenomena, coupled with methodological innovations in design and measurement approaches tailored to the study of such phenomena. The Hidden Costs of AI Interviews: Interview Anxiety and Performance Compared to Human Interviews Author: Yali Li; Nanjing University Author: Wei He; Nanjing University Author: Yangyi Chen; Nanjing University Author: Xiaoyue Wu; Nanjing University Unlocking the Role of Emotions in AI Interviews: Factors Shaping Applicant Reactions and Performance Author: Kang Yang Trevor Yu; Nanyang Business School Author: Kim Huat Goh; Nanyang Technological University Author: Yefei Feng; Nanyang Technological University Author: Tong Wu; Nanyang Technological University Author: Sitong YU; Nanyang Technological University AI in Recruitment: A Qualitative Analysis of Applicant Perceptions of Warmth and Competence Author: Federico Magni; Nanyang Technological University Author: Yaping Gong; The Hong Kong University of Science and Technology Autonomy- Versus Dependency-Oriented AI Usage and Their Effects on Employee Creativity Author: Maona Mu; North China University of Technology Author: Wenhao Luo; North China University of Technology Pay’s Breaking Point: When AI Undermines Pay Systems Author: Ormonde Cragun; University of Minnesota Duluth Author: Joseph Ernest Dalle Molle; University of South Carolina Author: Xiaoyue Wu; Nanjing University Interfacing Artificial Intelligence and Human Resource Management in New Firms Author: Ann-Sophie Hahn; Author: Luis F. Martinez; Author: Aristides Isidoro Ferreira;

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