The Behavioural Science of Using AI in HRM Decision-Making: When It Helps and When It Goes Wrong

Citation

Anderson CG (2024) The Behavioural Science of Using AI in HRM Decision-Making: When It Helps and When It Goes Wrong. In: Teresa Del Val Nunez M, Yela Aranega A & Ribeiro-Soriano D (eds.) Artificial Intelligence and Business Transformation. Contributions to Management Science. Cham: Springer Nature Switzerland, pp. 229-243. https://doi.org/10.1007/978-3-031-58704-7_14

Abstract
This chapter demonstrates how behavioural science can be used in identifying opportunities and costs of applying Artificial Intelligence (AI) in human resource management (HRM). The digitisation of HRM has examples of behavioural biases informing their design. Similarly, the use of AI, as an extension of the digitisation of HRM can also have heuristic rule-based decision-making determining their design. At the same time, behavioural science has also been used to support HRM in the context of behavioural biases, cognitive biases, and heuristic rule-based decision-making. With the synergy between cognitive bias, and heuristic rule-based decision-making, behavioural science has been used to consider the opportunities and costs in applying AI. This chapter combines the literature on AI and HRM, as well as behavioural science and AI, to provide a novel tool for considering the opportunities and costs of applying AI in HRM. The analysis at the intersection of behavioural science, AI, and HRM is gives illustrative examples and debates the opportunities and costs of applying AI in HRM from the perspective of behavioural science. The examples given can be used for further application of behavioural science as a tool for considering the opportunities and costs in applying AI in HRM.