This project investigates the relationship between input detail and output bias in AI generative tools, using MidJourney as a case study. By incrementally refining prompts, the work demonstrates how minimal inputs often produce biased or inaccurate images, while more comprehensive inputs yield balanced, precise, and ethically aligned results. Through a video-based exploration of image evolution, the project highlights both the transformative potential of AI in creative practices and the indispensable role of human agency in guiding these tools responsibly.