ALGORITHMIC FAIRNESS AND ETHICS IN DECISION MAKING

Because machine learning and artificial intelligence are being used more and more in a variety of fields, algorithmic fairness and ethics in decision making have attracted a lot of interest in recent years. This abstract gives a succinct overview of the major ideas and problems surrounding algorithmic ethics and fairness in decision-making. It emphasises how crucial it is to address the prejudice, discrimination, and moral issues raised by algorithmic decision-making systems. The necessity for fairness-aware algorithms, fairness measures, and transparency in decision-making processes are also mentioned in the abstract. Additionally, it highlights how the area is interdisciplinary and how cooperation between researchers, policymakers, and practitioners is essential for creating and implementing just and moral algorithms. Overall, this abstract provides a succinct overview of the larger subject of algorithmic fairness and ethics, laying the groundwork for future investigation and research in this important area