Imagine an AI that can create stunning visuals from any text prompt. That's the power of text-to-image diffusion models. But what if those prompts lead to undesirable or even harmful outputs? New research introduces EIUP, an innovative approach to enhance the safety of AI image generation. The challenge lies in the subtle nature of some unsafe prompts. Seemingly harmless phrases can sometimes result in not-safe-for-work (NSFW) content or images that infringe on copyrights. Traditional methods, like prompt filtering or retraining the AI model, are resource-intensive and can compromise the model's overall performance. EIUP offers a smarter solution. By introducing a separate "erasure prompt," this technique pinpoints and neutralizes specific unwanted elements within the image generation process. This works by focusing on the interplay between text and image. The erasure prompt guides the AI to identify and suppress visual features associated with unsafe content, leaving the rest of the image intact. Think of it like an AI censor, working in real-time to prevent the generation of inappropriate content. EIUP represents a significant advancement in AI safety, addressing a critical challenge in image generation. Its efficient and targeted approach offers promising implications for responsible AI development.