TY - JOUR
T1 - Human resource management in the age of generative artificial intelligence
T2 - perspectives and research directions on ChatGPT
AU - Budhwar, Pawan
AU - Chowdhury, Soumyadeb
AU - Wood, Geoffrey
AU - Aguinis, Herman
AU - Bamber, Greg J.
AU - Beltran, Jose R.
AU - Boselie, Paul
AU - Cooke, Fang Lee
AU - Decker, Stephanie
AU - DeNisi, Angelo
AU - Dey, Prasanta Kumar
AU - Guest, David
AU - Knoblich, Andrew J.
AU - Malik, Ashish
AU - Paauwe, Jaap
AU - Papagiannidis, Savvas
AU - Patel, Charmi
AU - Pereira, Vijay
AU - Ren, Shuang
AU - Rogelberg, Steven
AU - Saunders, Mark N. K.
AU - Tung, Rosalie L.
AU - Varma, Arup
N1 - © 2023 The Authors.
PY - 2023/7/15
Y1 - 2023/7/15
N2 - ChatGPT and its variants that use generative artificial intelligence (AI) models have rapidly become a focal point in academic and media discussions about their potential benefits and drawbacks across various sectors of the economy, democracy, society, and environment. It remains unclear whether these technologies result in job displacement or creation, or if they merely shift human labour by generating new, potentially trivial or practically irrelevant, information and decisions. According to the CEO of ChatGPT, the potential impact of this new family of AI technology could be as big as ?the printing press?, with significant implications for employment, stakeholder relationships, business models, and academic research, and its full consequences are largely undiscovered and uncertain. The introduction of more advanced and potent generative AI tools in the AI market, following the launch of ChatGPT, has ramped up the ?AI arms race?, creating continuing uncertainty for workers, expanding their business applications, while heightening risks related to well-being, bias, misinformation, context insensitivity, privacy issues, ethical dilemmas, and security. Given these developments, this perspectives editorial offers a collection of perspectives and research pathways to extend HRM scholarship in the realm of generative AI. In doing so, the discussion synthesizes the literature on AI and generative AI, connecting it to various aspects of HRM processes, practices, relationships, and outcomes, thereby contributing to shaping the future of HRM research.
AB - ChatGPT and its variants that use generative artificial intelligence (AI) models have rapidly become a focal point in academic and media discussions about their potential benefits and drawbacks across various sectors of the economy, democracy, society, and environment. It remains unclear whether these technologies result in job displacement or creation, or if they merely shift human labour by generating new, potentially trivial or practically irrelevant, information and decisions. According to the CEO of ChatGPT, the potential impact of this new family of AI technology could be as big as ?the printing press?, with significant implications for employment, stakeholder relationships, business models, and academic research, and its full consequences are largely undiscovered and uncertain. The introduction of more advanced and potent generative AI tools in the AI market, following the launch of ChatGPT, has ramped up the ?AI arms race?, creating continuing uncertainty for workers, expanding their business applications, while heightening risks related to well-being, bias, misinformation, context insensitivity, privacy issues, ethical dilemmas, and security. Given these developments, this perspectives editorial offers a collection of perspectives and research pathways to extend HRM scholarship in the realm of generative AI. In doing so, the discussion synthesizes the literature on AI and generative AI, connecting it to various aspects of HRM processes, practices, relationships, and outcomes, thereby contributing to shaping the future of HRM research.
KW - artificial intelligence
KW - ChatGPT
KW - CSR
KW - ethics
KW - generative AI
KW - HRM
KW - human resource strategy
KW - international human resource management
KW - productivity
KW - sustainability
U2 - 10.1111/1748-8583.12524
DO - 10.1111/1748-8583.12524
M3 - Article
SN - 0954-5395
VL - 33
SP - 606
EP - 659
JO - Human Resource Management Journal
JF - Human Resource Management Journal
IS - 3
ER -