The recent developments in the field of AI regulation and algorithmic bias mitigation are significantly advancing the integration of ethical considerations into AI systems. There is a growing emphasis on ensuring fairness, transparency, and accountability in AI models, particularly in high-stakes applications such as personnel assessment and selection. The field is moving towards a more interdisciplinary approach, with collaborations between organizational researchers, computer scientists, and data scientists to develop comprehensive frameworks for bias mitigation. Additionally, regulatory frameworks are being critically examined and compared globally, with a focus on aligning AI systems with human rights and ethical standards. The European Union's Artificial Intelligence Act is a notable example, prompting research into compliance strategies for complex AI models like Graph Neural Networks. Furthermore, there is a call for a human rights-based approach to AI, particularly in sensitive areas like computer vision, to address and prevent human rights violations. This holistic approach aims to create AI systems that are not only technologically advanced but also socially responsible and ethically sound.