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CFP - Artificial Intelligence and Human Resource Management

  • 1.  CFP - Artificial Intelligence and Human Resource Management

    Posted 02-23-2024 16:49

    Artificial Intelligence and Human Resource Management



    PROPOSAL DEADLINE: July 1, 2024 

    FINAL PAPER DEADLINE:  February 1, 2025

    Issue in Research in Human Resource Management Peer Reviewed Series



    Craig Van Slyke, Louisiana Tech University, vanslyke@latech.edu,  

    Kimberly Lukaszewski, Wright State University, kimade611@hotmail.com


    In late November 2022, Open AI released ChatGPT, the first generative artificial intelligence system in wide use by the general public. Since that watershed moment, generative AI has begun affecting virtually every corner of management, including human resource management (HRM). Human resource professionals, like most knowledge workers, must learn to navigate the changes brought on by generative AI (GAI), and the multitude of changes made in HRM by AI and Machine learning (ML).   

    Although GAI is new, HRM has been using other forms of artificial intelligence for many years. For example, machine learning algorithms have been assisting with candidate selection, performance evaluation, recruitment, and other aspects of HRM for many years. In contrast with chat-based GAI, traditional systems often acted in the background, carrying out tasks often without users being explicitly aware that AI was in the mix. For example, a recruiting manager who reviews a short list of candidates may not realize that a machine learning algorithm determined which candidates made the short list.

    Clearly, AI's and GAI's impact on the practice of HRM will only increase in the coming years. For example, AI will be used to attract applicants, hire employees, conduct training, compensate them, and manage their performance. Similarly, GAI will be used to write job descriptions, recruitment ads, selection simulations, training materials and performance appraisals. As a result, the impact of AI needs to be understood in the larger context of HRM. HRM is undergoing significant changes such as the changing nature of work, the tension between remote work and "return to office" initiatives, increasing challenges related to diversity and inclusion, among others. AI is also expected to eliminate many jobs in the next few years. For instance, a Goldman Sachs report indicated that 300 million jobs around the world will be disrupted by AI, and McKinsey estimated that, at least, 12 million Americans would have to change to another field by 2030 (https://www.businessinsider.com/ai-radically-reshape-job-market-global-economy-employee-labor-innovation-2023-8.) Thus, HRM must be able to deal with these dramatic changes.

    Because of these factors, sound, careful thinking and rigorous research are needed to better understand the potential impacts of AI on HRM, and how the benefits of AI can be maximized while its risks are minimized. This special issue will highlight research that can help guide practice and future research as we prepare for the brave new world of AI-infused HRM.

    Topics of interest include, but are not limited to:

    ·       The effectiveness of AI changes to HRM practices (e.g., selection, training)

    ·       Ethical challenges related to the use of AI in human resource management

    ·       Mitigation of ethical issues associated with AI-enhanced human resource management

    ·       Employee and applicant reactions to the use of AI in human resource management

    ·       Legal issues surrounding the use of AI in human resource management

    ·       The positive and negative impacts of AI on bias, justice, and inequity in human resource management

    ·       Changing roles of human resource professionals in AI-driven human resource management environments

    ·       Ensuring transparency and accountability in AI-enhanced human resource management

    ·       Impacts of AI on recruitment and/or selection

    ·       Implications of AI for training, performance management, and compensation

    ·       Effects of AI on the design of jobs  

    ·       How the use of AI will affect the skills needed by the workforce

    Submission Instructions

    Submissions should be limited to conceptual papers, systematic or integrative literature reviews with theory, conceptual development, or research implications, critiques of the literature or the field of HRM with implications, new theoretical models or research frameworks, or meta-analyses. In a few cases, empirical research will also be accepted for this special issue (contact Craig Van Slyke for approval.)  

    The editors would like to review your potential topic so we ask that you email a short (1 to 5  page) proposal to Craig Van Slyke (vanslyke@latech.edu) and Kimberly Lukaszewski (kimade611@hotmail.com) by July 1, 2024.

    If your proposal is accepted, then you should email your final paper to Craig Van Slyke and Kimberly Lukaszewski by Feb 1, 2025. 

    All final submissions are due Feb 1, 2025.

    Proposal guidelines: proposals should be no more than 5 pages and include (a) an introduction to the problem, question, or knowledge gap to be addressed by the paper, (b) a brief overview of the state of published knowledge, (c) a description of the approach or method the paper will present, and (d) the expected contribution(s) or implications arising from the paper. All proposals are due July 1, 2024.

    Final papers must be no more than 50 pages (approximately 12,500 words) including references and tables, and must conform to the 7th edition of the APA Publication Manual (October, 2020). They must also be double spaced in Word Format. Submission should also include an abstract. Authors will be asked to submit a 200-word bio and contact information with their submission.


    About Research in Human Resource Management (RHRM)

    RHRM is an annual peer-reviewed research series that is designed to advance theory, research, and practice on Human Resource Management, Organizational Behavior, Industrial and Organizational Psychology and related fields. The series publishes monographs, literature reviews, and new theoretical models as well as invited essays designed to foster research on a specific topic. We also accept empirical research on some select topics. It uses a double blind review process. A list of editorial board members is provided on the series website (https://www.infoagepub.com/series/Research-in-Human-Resource-Management). Issues and abstracts can also be seen at www.diannastone.com. RHRM is listed in Cabell's Directory and is indexed in the EBSCOhost eBook Business Collection, and PsyINfo.