This chapter on Ethical AI Testing and Evaluation, explores the critical role of testing and evaluation in ensuring that AI systems align with ethical principles such as fairness, transparency, accountability, and privacy. The chapter emphasizes the integration of ethical considerations into the AI development lifecycle, particularly through modern software development practices like Continuous Integration (CI), Continuous Deployment (CD), and DevOps. It introduces frameworks, tools, and methodologies for ethical testing, including fairness testing, bias detection, explainability validation, and privacy audits. The chapter also highlights the importance of iterative testing, stakeholder engagement, and continuous ethical impact assessments to address evolving societal norms and regulatory requirements. A case study on chatbot testing illustrates the practical application of these principles, showcasing how ethical and technical testing intersect to create responsible AI systems.