Author: Kumarakulasingam Brasanan

Doi: 10.26480/mjhrm.01.2025.53.56

This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Using Artificial Intelligence (AI) more in Human Resource Management (HRM) can bring many advantages such as making processes faster, more fair, and able to handle larger tasks effectively. However, this change in technology has also brought some new problems, especially biased algorithms. This review looks at how bias appears in AI-based HR systems, especially in hiring, performance reviews, and workforce data analysis. Utilizing inquire about from diverse areas, real-life illustrations, and speculations, this paper looks at how inclination is built into information, how calculations are planned, and how they are utilized. Imperative illustrations, like Amazon’s stopped AI contracting instrument and facial examination utilized by HireVue, appear how these innovations can proceed to make shamefulness based on gender, race, and financial status. The review points out a few reasons for unfairness, such as training data that doesn’t include everyone, unclear algorithms, and no responsibility when putting systems into use. It also looks closely at current laws and ethical rules, pointing out that they are not enough to deal with the complicated issues of bias in artificial intelligence in human resources management.