Writing Question
Overview of my proposed dissertation topic The topic I am proposing for my dissertation is “Organizational Accountability and Preparedness in Addressing Ethical Implications of AI in Human Resource Management Practices”. The growing adoption of Artificial Intelligence (AI) in hiring processes by organizations has raised several important issues. These primarily pertain to ethical concerns, potential biases, the transparency of procedures, accountability, and AI’s significant impact on Human Resource Management (HRM) practices. My research focuses on exploring the extent of responsibility that organizations uphold in light of the ethical dilemmas presented by AI usage, as well as their preparedness to address such challenges. Overview of the Theories related to the topic The increasing integration of Artificial Intelligence (AI) in recruitment practices by companies has brought to the forefront various issues. These issues are primarily associated with the ethical aspects, potential biases, clarity of processes, responsibility, and the overarching influence of AI on Human Resource Management (HRM) practices. My research aims to delve into the level of accountability that organizations maintain considering the ethical quandaries posed by AI usage, as well as their readiness to face such challenges. A study published in the Journal of Student Research (Mariani & Lozada, 2023) examining AI and algorithmic decision-making in workplace recruitment indicates that more work is needed to understand HR professionals’ attitudes towards the “liability risk” associated with the implementation of AI in recruitment. This study also highlights the necessity for research into how various regions or countries are tackling AI-induced challenges in HR through regulations and policies. In a similar vein, a paper in the Journal of Business Ethics by Hunkenschroer and Luetge (2022) argues that the existing measures to mitigate ethical risks in recruitment are too broad and lack specific, practical guidelines for domain-specific implementation. How topic relate to goal of the academic program One of the goals of my academic program i.e. Information Technology is to Promote critical thinking and problem-solving skills to include leadership at the organizational and system level and the ability to evaluate and improve the quality and safety of Information Sciences. My research aims to enhance critical thinking and problem-solving skills in the realm of Information Sciences, with a focus on leadership at both organizational and systemic levels. This includes assessing and improving the quality and safety of Information Sciences, particularly in AI-driven recruitment. It critically examines the ethical implications of AI in recruitment, a pressing issue in this field. The research delves into how organizations navigate complex, technology-driven environments, specifically how their decision-making influences the quality and ethical standards of AI systems in the recruitment process. Similarly, another goal is to Instill ethical leadership, service, and values. My research emphasizes the importance of instilling ethical leadership and values, aligning with the goal of nurturing ethical responsibility in AI technology development and implementation. This focus on ethical dilemmas, accountability, and transparency directly addresses the challenges in AI-driven recruitment, such as potential biases and privacy issues. The aim is to foster a sense of ethical responsibility, essential for guiding decisions and actions in the evolving landscape of AI in hiring processes, thereby ensuring ethical standards and leadership in Information Sciences. Methodology and study design The methodology for this quantitative study involves selecting a sample from a large and diverse population across various schools, districts, or organizations. The target population is comprised of professionals involved in the recruitment process, including talent acquisition specialists and IT professionals, as well as those affected by recruitment practices, such as recent employees who have undergone AI-driven recruitment processes. This group also includes legal professionals knowledgeable about employment and privacy laws. The approximate size of the target population will be determined using resources like the U.S. Bureau of Labor Statistics (BLS). Recruitment for the study will take place in specific organizations, social media groups, or sites where these professionals are likely to be found. For studies not involving live subjects, the focus will be on gathering archival raw data from relevant locations. Data collection for this study will primarily involve my professional network and the use of online platforms such as LinkedIn.com to recruit the sample population. This approach will enable access to a wide range of professionals who directly or indirectly interact with AI in recruitment processes. Additionally, I plan to explore legal forums or groups specializing in employment law to further diversify the sample. This strategy ensures a comprehensive collection of data from a variety of sources, providing a well-rounded perspective on the impact and implications of AI in recruitment practices. References Mariani, K., & Lozada, F. V. (2023). The use of AI and algorithms for decision-making in workplace recruitment practices. Journal of Student Research, 12(1). https://doi.org/10.47611/jsr.v12i1.1855 Hunkenschroer, A. L., & Luetge, C. (2022). Ethics of AI-Enabled Recruiting and Selection: A Review and Research agenda. Journal of Business Ethics, 178(4), 977– 1007. https://doi.org/10.1007/s10551-022-05049-6
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