Emotional Conveyance Analysis of Artificial Intelligence Painting

AI-generated content inherits the strengths of Professional-Generated Content (PGC) and User-Generated Content (UGC) while fully leveraging technological advantages to forge innovative digital content generation and interaction. With the continuous evolution of technology, AI painting techniques have sparked widespread discussions in the realm of creative expression. Artificial intelligence technology, driven by its ability to comprehend semantics, facilitates the conversion of images and conveys semantic emotions. It also contributes to establishing a robust human-machine interactive relationship, albeit accompanied by certain ethical risks. This study employs emotional measurement experiments and eye-tracking technology. By analyzing individuals' assessments of emotional mixed-image collections and correlating the results with experimental eye-tracking data and dominant color patterns within the images, the paper investigates the accuracy of AI-generated tools in transcribing emotional nuances. Furthermore, it delves into the synergistic relationship between humans and machines within the context of artistic creation and explores the dynamics of their interaction.