Generative AI has emerged as one of the most transformative technologies of our time, capable of creating text, images, audio, video, and code that increasingly resembles human-created content. While these capabilities offer tremendous potential, they also raise profound ethical questions. Key ethical considerations include bias and fairness, as generative AI systems learn from existing data which inevitably contains societal biases; misinformation and manipulation concerns related to deepfakes, synthetic media, and automated disinformation; intellectual property and attribution questions about training data rights, output ownership, and impacts on creative labor; and privacy concerns including training data privacy, synthetic identity creation, and enhanced surveillance capabilities. Addressing these ethical considerations requires multifaceted approaches including technical solutions, policy and regulatory approaches, responsible organizational practices, and individual and collective responsibility.