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Human resource management in the age of generative artificial intelligence: perspectives and research directions on ChatGPT

Journal: Human Resource Management Journal

Date: 2023

Author: Pawan Budhwar, Soumyadeb Chowdhury, Geoffrey Wood, Herman Aguinis, Greg J. Bamber, Jose R. Beltran, Paul Boselie, Fang Lee Cooke, Stephanie Decker, Angelo DeNisi, Prasanta Kumar Dey, David Guest, Andrew J. Knoblich, Ashish Malik, Jaap Paauwe, Savvas Papagiannidis, Charmi Patel, Vijay Pereira, Shuang Ren, Steven Rogelberg, Mark N. K. Saunders, Rosalie L. Tung, Arup Varma

Abstract:
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.

Link: Google Scholar

Background and Context

Article Overview

This invited review brings together perspectives from 26 leading HRM scholars on how generative AI, particularly ChatGPT, is transforming human resource management practices and research.

Timely Discussion

Published shortly after ChatGPT's public release, this paper examines the rapidly evolving landscape of AI technologies that can generate human-like responses to queries and produce sophisticated content.

Research Approach

The paper synthesizes 11 expert perspectives covering topics from business implications and ethics to research methods, presenting a comprehensive overview of generative AI's impact on HRM.

Evolution of GPT Models Shows Rapidly Increasing Capabilities

GPT-1 (2018) Basic language model GPT-3 (2020) 175 billion parameters ChatGPT (2022) Human-like interaction GPT-4 (2023) Multi-modal capability
  • GPT models have evolved rapidly from basic language processing to sophisticated multi-modal capabilities in just five years.
  • ChatGPT marked a pivotal transition with its human-like conversational ability and widespread public availability.
  • Each iteration brings exponential improvements in parameters and capabilities, raising both opportunities and concerns for HRM.

Generative AI Will Transform Core HRM Functions and Practices

HRM Recruitment Performance Training Analytics Employee Relations EDI
  • Generative AI will impact all core HR functions from recruitment and training to performance management and analytics.
  • Each HR function will face unique challenges and opportunities when integrating AI tools like ChatGPT.
  • The interconnected nature of HR functions means AI adoption in one area will cascade effects to others.

The Dual Nature of ChatGPT: Opportunities vs. Challenges for HRM

Opportunities Challenges Increased Productivity & Efficiency Enhanced Data-Driven Decision Making Personalized Employee Experiences Focus on Strategic HR Activities Algorithmic Bias & Discrimination Privacy & Data Security Concerns Job Displacement & Skill Gaps Ethical & Governance Issues
  • ChatGPT presents a dual nature in HRM, offering significant advantages while introducing new risks and challenges.
  • Productivity benefits must be balanced against potential bias and discrimination issues inherent in AI systems.
  • Organizations must develop governance frameworks to maximize opportunities while mitigating ethical and privacy risks.

Framework for Sustainable HRM in the Age of Generative AI

Sustainable HRM with Generative AI Economic Performance Productivity & Efficiency Social Performance Employee Well-being Environmental Performance Resource Efficiency
  • Sustainable HRM requires balancing economic, social, and environmental performance dimensions when implementing generative AI.
  • Organizations must consider energy consumption and carbon footprint of large AI models against productivity benefits.
  • Employee well-being must remain central to AI adoption decisions to ensure truly sustainable HR practices.

Key Recommendations for HR Professionals Adopting Generative AI

Trust, but Verify Approach Verify AI outputs Maintain human oversight Acknowledge AI use Ethical framework Retrain employees Focus on strategy
  • HR professionals must verify AI outputs and maintain human oversight, treating AI as an assistant rather than replacement.
  • Organizations should establish ethical frameworks governing AI use in HR processes to prevent misuse and bias.
  • Employees need retraining to work alongside AI tools, developing skills that complement rather than compete with automation.

Contribution and Implications

  • Generative AI will transform HRM by automating routine tasks while creating new challenges around ethics, fairness, and governance.
  • Organizations need balanced strategies to leverage AI capabilities while mitigating risks related to bias, privacy, and job displacement.
  • Research must examine AI integration into HR processes, developing frameworks for responsible and sustainable technology adoption.
  • HR professionals require new competencies including AI literacy, ethical oversight, and strategic focus to succeed in this evolution.

Data Sources

  • Visualization 1 is based on Figure 1 from the paper showing the evolution of GPT models from 2017 to 2023.
  • Visualization 2 synthesizes information from across multiple perspectives in the paper discussing impacts on HR functions.
  • Visualization 3 draws from sections on opportunities and challenges of generative AI for HRM across perspectives.
  • Visualization 4 is inspired by Figure 5 in the paper related to sustainable HRM and productivity performance dimensions.
  • Visualization 5 consolidates recommendations from the "Trust, but verify" methodology section and overall paper conclusions.