As Artificial Intelligence (AI) and machine learning become increasingly integrated into everyday life, addressing their ethical implications and potential biases is crucial. This article reviews key concerns about ethics, governance, bias reduction, and privacy in AI-ML applications. While these systems show remarkable capabilities in areas like image recognition, natural language processing, and analytics, they also risk producing unfair outcomes due to biases from sources such as training data, algorithms, feature selection, and institutional practices. A comprehensive evaluation from development to deployment is essential to ensure AI systems are fair, transparent, and beneficial. This review highlights the importance of responsible development and use of AI technologies.