Artificial intelligence (AI) in education is a field of study that integrates the applications of machine learning, technological tools, algorithm productions, and natural language processing. Recently, there has been a surge of AI technologies such as ChatGPT and personalized learning platforms to help students’ learning, assessment systems to support faculty and students, and other systems to generate deeper understanding of students’ behavior. Despite the benefits of AI technologies in education to support students’ learning experiences, and best practices for faculty, there are concerns about the ethical and privacy challenges associated with the application of these AI technologies in higher education settings. Further, not much is known about the ethical and privacy in AI education and challenges students and faculty experience with the use and application of AI technologies, implications on students and faculty, and its challenges in higher education institutions. This chapter provides a comprehensive exploration of the key ethical and privacy issues raised by the use of AI in higher education, including algorithmic bias and fairness, transparency and explainability, accountability and human oversight, data privacy and security, and student autonomy and consent. We analyze how these challenges can impact student learning, academic performance, well-being, and the comprehensive educational experience, with particular attention to the differential effects on vulnerable and underrepresented student populations. The chapter also examines the crucial role of institutional policies, governance frameworks, and participatory design practices in mitigating risks and fostering trust. Finally, we offer actionable recommendations for addressing these challenges through a combination of technical, educational, and policy interventions, and highlight priority areas for future research and collaboration. The chapter also examines the crucial role of institutional policies, governance frameworks, and participatory design practices in mitigating risks and fostering trust. Finally, we offer actionable recommendations for addressing these challenges through a combination of technical, educational, and policy interventions, and highlight priority areas for future research and collaboration. By proactively engaging with the ethical and privacy implications of AI, higher education institutions can harness the benefits of these powerful technologies while upholding fundamental values of fairness, transparency, accountability, and respect for student rights and agency. Recommendations for future studies and a conclusion are discussed.