The rise of artificial intelligence (AI) in dermatology introduces both groundbreaking innovations and pressing ethical dilemmas. From AI-driven clinical decision support tools (AI-CDS) used directly by patients to ambient AI scribes assisting clinicians, these technologies promise enhanced diagnostic accuracy, efficiency, and access. However, ethical concerns emerge around algorithmic bias, transparency, accountability, and safety. AI systems frequently rely on datasets dominated by lighter skin tones, leading to potential misdiagnoses in skin of colour and perpetuating health disparities. The opacity of deep learning models—the so-called “black box” problem—limits explainability, while the absence of regulatory oversight, particularly for direct-to-consumer tools, raises serious concerns about nonmaleficence and misinformation. Additionally, while AI scribes offer relief from burdensome documentation and have been associated with improved physician–patient interactions, they still require rigorous quality control and ongoing human supervision. This chapter explores these multifaceted ethical challenges and advocates for a framework grounded in justice, inclusivity, transparency, explainability, and patient autonomy. A collaborative, interdisciplinary approach is essential to align AI implementation in dermatology with ethical integrity and clinical safety.