Generative Artificial Intelligence (AI) refers to models that can create novel content such as text, images, music, code, or synthetic data. In recent years, Generative AI techniques—from Generative Adversarial Networks (GANs) to large language models and image diffusion models—have advanced rapidly, demonstrating unprecedented capabilities in mimicking human-like creativity. These developments offer exciting innovations, but they also raise serious ethical challenges. As Generative AI becomes more integrated into society, concerns have emerged around how to use this technology responsibly and mitigate potential harms. Key issues include the potential for models to learn and amplify biases present in training data, to produce misinformation or deceptive content, to infringe on privacy and data protection, and to create synthetic media (deepfakes) that undermine trust. The ethical implications are complex and multifaceted, touching on fairness, accountability, transparency, and even the foundations of truth in democratic societies.