Human resource management in the age of generative artificial intelligence

Perspectives and research directions on ChatGPT

Bibliographic Data

ID23369166
AuthorsPawan Budhwar (0000-0001-8915-6172, Aston University Birmingham UK), Soumyadeb Chowdhury (0000-0002-8074-248X, Information, Operations and Management Sciences Department TBS Business School Toulouse France, corresponding author), Geoffrey Wood (0000-0002-6690-338X, DAN Department of Management & Organizational Studies Western University London Ontario Canada), Herman Aguinis (0000-0002-3485-9484, School of Business The George Washington University Washington District of Columbia USA), Greg J Bamber (0000-0001-6646-3065, Monash Data Futures Institute Monash University Melbourne Australia), Jose R Beltran (0000-0002-3886-8142, Department of Human Resources & Organizational Behavior School of Business Rutgers University‐Camden Camden New Jersey USA), Paul Boselie (0000-0001-8507-7258, Utrecht University School of Governance Utrecht University Utrecht The Netherlands), Fang Lee Cooke (0000-0003-0337-6591, Monash Business School Monash University Melbourne Australia), Stephanie Decker (0000-0003-0547-9594, Department of Strategy & International Business Birmingham Business School University of Birmingham Birmingham UK), Angelo S Denisi (Tulane University), Angelo DeNisi (Tulane University A.B. Freeman School of Business New Orleans Los Angeles USA), Prasun Kanti Dey (0000-0002-9984-5374, Aston University), Prasanta Kumar Dey (Operations and Information Management Department Aston Business School College of Business and Social Science Aston University Birmingham UK), Deryn Guest (0000-0003-0457-6077, King's Business School King's College London London UK), Andrew J Knoblich (Department of Organizational Science University of North Carolina at Charlotte Charlotte North Carolina USA), Ashish Malik (0000-0002-2185-7674, College of Human and Social Futures Newcastle Business School The University of Newcastle (UON) Ourimbah NSW Australia), Jaap Paauwe (0000-0003-3633-9607, Human Resource Studies Tilburg University Tilburg The Netherlands), Savvas Papagiannidi (0000-0003-0799-491X, Newcastle University Business School Newcastle Upon Tyne UK), Charmi Patel (0000-0002-0235-9784, Henley Business School University of Reading Reading UK), Vijay Pereira (0000-0001-6755-0793, NEOMA Business School Reims France), Shuang Ren (0000-0002-8768-8447, Queen's Business School Queen's University Belfast Belfast UK), Steven G Rogelberg (University of North Carolina at Charlotte), Steven Rogelberg (Department of Organizational Science University of North Carolina at Charlotte Charlotte North Carolina USA), Mark N K Saunders (0000-0001-5176-8317, Department of Management Birmingham Business School University of Birmingham Birmingham UK), Rosalie L Tung (Simon Fraser University Burnaby British Columbia Canada), Arup Varma (0000-0002-6530-5564, Quinlan School of Business Loyola University Chicago Illinois USA)
Year2023
Volume33
Issue3
Pages606-659
Publication date2023-07-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueHuman Resource Management Journal (JOURNAL)
Journal identifiersISSN: 0954-5395 • E-ISSN: 1748-8583
PublisherWiley (PUBLISHER • GB)
DOI10.1111/1748-8583.12524
OpenAlexW4383913712
LanguageEN
Citations received72
References cited100

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.

Context (archaeology) · Engineering ethics · Generative grammar · Knowledge management · Political science · Public relations · Realm · Scholarship · Sociology · Stakeholder · AI and HR Technologies · Artificial Intelligence · Artificial Intelligence in Healthcare and Education · Computer Science · Engineering · Ethics and Social Impacts of AI · Law

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