This paper articulates a framework on responsible AI, focusing on the TAFES framework, standing on principles of Transparency, Accountability, Fairness, Ethics, and Safety. Taken as a practical use-case, the paper reviews the application of these principles in the design and implementation of an AI-powered diagnostic tool for the early detection of skin cancer in the context of health care. TAFES principles may be applied to the lifecycle of Generative AI use-cases, which faces major challenges: bias, data privacy, lack of explainability, and ethics in various applications, especially in health care. The paper illustrates the application of the guiding principles of TAFES with a hypothetical use-case of an AI-powered diagnostic tool for early skin cancer detection. Following the analysis of such a scenario, the paper concludes with a manifesto that of how policymakers, developers, users, and other stakeholders may harness the transformative power of AI through empathic mitigation of risks to human well-being and essential societal values.