Beyond Algorithms: Ethical Implications of AI-Driven Human Resources and Use of Employee Data
Abstract
Beyond Algorithms: Ethical Implications of AI-Driven Human Resources and Use of Employee Data
By Linda A. Stone
University of South Carolina - Upstate
TPC Generative AI & ChatGPT – MSBAU796-01F-Spring-2024
Dr. Uma Gupta
Abstract
The advent of Artificial Intelligence (AI) technologies has introduced a new, transformative era of data-driven decision-making opportunities for organizations of all sizes and industries. The impact of AI in the world of work and on society in general is pervasive. With these technological advancements, companies are grappling with the challenges of responsibly managing data, including employee data. This research paper presents an overview of AI in Human Resources (HR), algorithmic applications in HR, and people analytics, then explores the ethical considerations surrounding the use of AI in handling employee data within HR practices. To narrow the focus of this paper, it does not delve into the legal and regulatory requirements or strategies for use of AI in HR. The paper begins by outlining the current landscape of AI in HR, highlighting innovative use cases of employee data in areas such as talent acquisition, performance management, learning and development, and HR support. It introduces and acknowledges the ethical concerns that arise, including data privacy, consent, risk of bias, and presents a review of ethical frameworks and governance practices for AI in HR. The paper spotlights four areas of perhaps the most profound ethical concerns: privacy, bias, performance management and recruitment and selection of employees. While the paper introduces the landscape of risks, concerns, and potential pitfalls of machine learning in HR, it also presents an optimistic perspective on solutions and ideas to help employers effectively address ethical challenges, and thereby unlock the vast potential of AI in the HR arena. HR is “in the driver’s seat” and has a unique opportunity to foster a more inclusive, fair, and supportive workplace while contributing to employee wellbeing. Considering there is a gap in research on the relationship between how employee data are handled and employee wellbeing, the paper will attempt to explore this connection and recommend future research to advocate for a proactive approach to the ethical use of AI in HR to achieve business objectives, enhance the overall employee experience, and set a new standard for HR practices in the digital age.
Keywords
Human Resources, Employee data, Artificial intelligence, Workforce analytics, HR technologies, People analytics, Ethics & privacy, Algorithmic management
Beyond Algorithms: Ethical Implications of AI-Driven Human Resources and Use of Employee Data
CASB 117
Beyond Algorithms: Ethical Implications of AI-Driven Human Resources and Use of Employee Data
By Linda A. Stone
University of South Carolina - Upstate
TPC Generative AI & ChatGPT – MSBAU796-01F-Spring-2024
Dr. Uma Gupta
Abstract
The advent of Artificial Intelligence (AI) technologies has introduced a new, transformative era of data-driven decision-making opportunities for organizations of all sizes and industries. The impact of AI in the world of work and on society in general is pervasive. With these technological advancements, companies are grappling with the challenges of responsibly managing data, including employee data. This research paper presents an overview of AI in Human Resources (HR), algorithmic applications in HR, and people analytics, then explores the ethical considerations surrounding the use of AI in handling employee data within HR practices. To narrow the focus of this paper, it does not delve into the legal and regulatory requirements or strategies for use of AI in HR. The paper begins by outlining the current landscape of AI in HR, highlighting innovative use cases of employee data in areas such as talent acquisition, performance management, learning and development, and HR support. It introduces and acknowledges the ethical concerns that arise, including data privacy, consent, risk of bias, and presents a review of ethical frameworks and governance practices for AI in HR. The paper spotlights four areas of perhaps the most profound ethical concerns: privacy, bias, performance management and recruitment and selection of employees. While the paper introduces the landscape of risks, concerns, and potential pitfalls of machine learning in HR, it also presents an optimistic perspective on solutions and ideas to help employers effectively address ethical challenges, and thereby unlock the vast potential of AI in the HR arena. HR is “in the driver’s seat” and has a unique opportunity to foster a more inclusive, fair, and supportive workplace while contributing to employee wellbeing. Considering there is a gap in research on the relationship between how employee data are handled and employee wellbeing, the paper will attempt to explore this connection and recommend future research to advocate for a proactive approach to the ethical use of AI in HR to achieve business objectives, enhance the overall employee experience, and set a new standard for HR practices in the digital age.