As AI-based technologies play an increasingly pivotal role in shaping dietary recommendations, there is a growing need to assess the ethical considerations surrounding privacy, data security, and potential biases inherent in these systems. The chapter investigates the ethical implications of incorporating artificial intelligence into nutritional guidance systems by thoroughly examining current literature, case studies, and empirical analyses and illuminates the diverse challenges linked with AI-powered nutritional guidance. The discussion explores the use of LIME as a technical methodology for enhancing algorithm transparency, interpreting model decisions, and addressing potential biases. Emphasizing the importance of transparent algorithms, robust privacy protocols, and unbiased model development, this research contributes to the ongoing discourse on how AI can be harnessed to promote healthier dietary practices while safeguarding user privacy and minimizing biases. The book chapter also delves into the robust privacy protocols and unbiased model development to ensure responsible deployment. By examining real-world examples and proposing ethical frameworks, this research contributes to the ongoing discourse on how AI can be harnessed to promote healthier dietary practices while safeguarding user privacy and minimizing potential biases. In conclusion, the chapter lays the foundation and perspectives for policymakers, developers, and stakeholders to enhance AI applications for nutrition in a morally responsible way.