Abstract
By corporations applying the ethical framework of Rawls justice and fairness and critical race theory (CRT) to artificial intelligence (AI) for hiring, employers can help to ensure that AI systems are used in a fair and just manner and that the rights of workers are protected. AI has become an integral part of modern hiring processes, promising efficiency, objectivity, and data-driven decision-making. However, concerns regarding AI discrimination in hiring have emerged as a critical ethical and societal issue. This chapter delves into the complex dynamics of AI-driven hiring discrimination, exploring its root causes, consequences, and potential solutions. The chapter further provides a comprehensive analysis of AI discrimination in hiring and a best practice rooted in CRT and the ethical framework of Rawls justice and fairness.
TopSignificance Of The Paper
The study on AI discrimination in hiring is significant because it highlights the potential risk of using AI in hiring (Pessach & Shmueli, 2021). The research conducted on the issue of AI bias in the context of employment selection holds considerable importance as it sheds light on a plausible hazard associated with the utilization of AI technology in the recruiting process (Hunkenschroer & Kriebitz, 2023). AI systems, similar to human beings, possess the potential for discrimination, which may result in discriminatory treatment towards specific demographic groups (SHRM, 2021).
The information from the paper may also be helpful to organizations in order to mitigate discrimination in AI (Lewis, 2023). There are several mechanisms through which AI systems can exhibit bias. One potential issue with ML systems is the presence of bias in the training data or decision-making algorithms (Kerasidou, 2021; Prescott, 2023). Furthermore, it is important to acknowledge that the individuals responsible for the design and implementation of AI systems may own unconscious biases, which can potentially manifest inside the system itself. The following paragraph discusses methodology.
Key Terms in this Chapter
CRT: The work of progressive legal scholars of color who are attempting to develop a jurisprudence that accounts for the role of racism in American law and that works toward the elimination of racism as part of a larger goal of eliminating all forms of subordination ( Matsuda, 1990 ; Solorzano, 1997 ). A central tenet of CRT is that institutions and everyday practices normalize racism and render it invisible ( Delgado & Stefancic, 2001 ; Golash-Boza et al., 2019 ; Yosso & Solorzano, 2007 ). The CRT movement transforms the relationship among race, racism, and power.
Ethics: The systematic study of the principles of right and wrong behavior, and morals ( Johnson, 2021 ).
Hiring: It encompasses all aspects of hiring new individuals to work for a company ( SHRM, 2021 ).
Discrimination: The unfair or prejudicial treatment of people and groups based on characteristics such as race, gender, age, or sexual orientation ( American Psychology Association, n.d. ).
Algorithmic Bias: Systematic and repeatable errors in a computer system that create unfair outcomes, such as privileging one category over another in ways different from the intended function of the algorithm.
Data Bias: A systematic tendency in which the methods used to gather data and generate statistics present an inaccurate, skewed, or biased depiction of reality.