This comprehensive review examines the use of artificial intelligence (AI) techniques to address algorithmic bias in job hiring. The study aims to analyze case studies, evaluate the impact of algorithmic bias, and explore strategies to mitigate it. Key findings include the effectiveness of vector space correction and data augmentation in natural language processing (NLP) and deep learning techniques for reducing bias. The research highlights the potential of AI in promoting fairness and diversity in hiring processes, emphasizing the need for collaboration between humans and AI. The study contributes to human resource practices by enhancing the fairness of hiring algorithms and advocating for ethical hiring tools. It also provides insights into the limitations and challenges of AI in eliminating bias, such as the quality of data and the complexity of detecting and addressing biases. Overall, the review underscores the importance of responsible AI practices and the need for continuous monitoring and evaluation to ensure fair and inclusive hiring practices.This comprehensive review examines the use of artificial intelligence (AI) techniques to address algorithmic bias in job hiring. The study aims to analyze case studies, evaluate the impact of algorithmic bias, and explore strategies to mitigate it. Key findings include the effectiveness of vector space correction and data augmentation in natural language processing (NLP) and deep learning techniques for reducing bias. The research highlights the potential of AI in promoting fairness and diversity in hiring processes, emphasizing the need for collaboration between humans and AI. The study contributes to human resource practices by enhancing the fairness of hiring algorithms and advocating for ethical hiring tools. It also provides insights into the limitations and challenges of AI in eliminating bias, such as the quality of data and the complexity of detecting and addressing biases. Overall, the review underscores the importance of responsible AI practices and the need for continuous monitoring and evaluation to ensure fair and inclusive hiring practices.