Adapting Imitation: Examining the Intersection of Art and AI Through a Comparative Study of Human and Machine Creativity

Abstract

This paper explores the intersection of art and artificial intelligence (AI) and investigates the potential impact of AI on the art world. Specifically, the author utilizes a diffusion model AI algorithm to generate synthetic images that replicate their own unique artistic style. The project is designed to train the AI on a dataset of the author's hand-made drawings and enable it to generate new artwork that closely matches their style. The paper discusses the effectiveness of the diffusion model AI algorithm and its ability to produce high-quality artwork based on textual prompts. The results demonstrate that the AI-generated artwork closely resembles the author's original hand-drawn pieces, highlighting the potential of AI to replicate artistic styles. The paper concludes by considering the ethical implications of AI-generated artwork and the need for artists to explore its capabilities and limitations to better understand its impact on the arts and society.