The fast use of artificial intelligence (AI) in hiring has led to a big problem. Sure, it brings a lot of efficiency, but there are also troubling ethical issues. More companies are turning to AI tools to streamline and automate their hiring processes. The lure of faster hiring, cost savings, and data-backed choices is appealing. Still, this shift comes with major hurdles, such as ongoing biases in algorithms, unclear decision-making, and serious concerns about data privacy. This paper digs deep into the complex effects of AI on hiring through a detailed research analysis using the PRISMA framework. It looks at information from academic articles, industry reports, and real-world business examples. The results show that while AI clearly helps with key metrics like how fast someone gets hired and the cost of hiring, it can also create and amplify biases that threaten diversity, equity, and inclusion efforts. There are significant worries about fairness, accountability, and legal compliance due to the opaqueness of many AI systems. The main contribution of this paper is a multi-faceted framework for the strategic and responsible use of AI in hiring. It argues that for companies to fully benefit from AI, they need to emphasize solid ethical principles, keep a human centered focus, and evolve from just implementing technology to building new capabilities for managing complex socio-technical systems.
Chappidi et al. (Thu,) studied this question.
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