Ethics in AI-Powered Hiring Platforms

Abstract

The paper under discussion focuses on the ethical issues arising from using AI in hiring technologies. Since organizations applied for more efficiency and cost control in employment through AI, significant ethical issues, including bias, transparency, accountability, and privacy, have arisen. The AI systems, which work on the rules of a continuously evolving data pattern, lead to the unearthing and possible enhancement of existing social prejudices, thus exploiting the originality of specific communities. Prejudice is again aggravated by the fact that the structure of many AI models is often not transparent, and candidates can have no idea why they have been hired. Additionally, accountability is ambiguous when AI-driven errors or discriminatory practices arise, raising questions about who bears responsibility. The developers, the employer or the data itself. It can be achieved only if a complex system implementation process is set based on the performed analysis. This, however, raises privacy issues because some AI hiring tools collect massive amounts of personal information, such as behavioural patterns from video interviews, in many cases without express informed consent. Based on the discussion in this paper, it is of paramount importance that AI is employed in hiring fairly and without prejudice, that processes involved in hiring through AI are clear, and that the privacy of the applicants is well protected. Using case analyses and theoretical discussions, it provides guidelines for managing ethical issues, such as using various training sets and human-in-the-loop. In conclusion, the paper calls for plausible use of AI in recruitment devoid of prejudice, bias, or infringement on the rights of the candidates for the sake of applying new technology.