Bias in Artificial Intelligence Systems - The Role of AI in Modern-Day Discrimination

This thesis critically investigates the ways in which artificial intelligence (AI) systems can contribute to discrimination, with a special focus on the recruitment and the data used in this process. While artificial intelligence (AI) has the potential to improve productivity and decision-making, it also runs the danger of enhancing and maintaining preexisting biases in the data used to train these systems. This research investigates the causes of bias in AI, including algorithmic, statistical, and cognitive biases, as well as how these biases affect the results of AI in a variety of industries. The study uses case studies to illustrate situations in which AI-driven hiring practices have produced unjust results and exacerbated socioeconomic, racial, and gender inequalities. The discussion of ethical issues pertaining to the use of AI in hiring highlights the necessity of openness, responsibility, and equity in AI design. In addition, the treatise suggests methods for identifying and reducing AI bias, highlighting the significance of multidisciplinary cooperation in the creation of ethical AI systems. The results have important ramifications for the creation and application of AI, especially in terms of making sure that these tools are in line with justice and fairness standards and don't worsen social injustices.