This paper presents a diffractive analysis of prompt-based generative AI, exploring its potential role in artists' creative practice. Seven visual artists were given access to a personalized instance of Stable Diffusion, fine-tuned on their own artwork. The analysis identified two dominant modes of use: AI for ideation and AI for production. The study highlights the ethical design considerations for the future development of generative AI interfaces. The paper discusses the ethical and moral dilemmas raised by Text-to-Image (TTI) systems, including issues of copyright, plagiarism, artistic merit, and economic implications. It also examines the impact of AI on the role of the human creator and broader cultural implications. The study emphasizes the importance of developing clear and rigorous guidelines for the building and implementation of generative AI technologies. The paper draws inspiration from Karen Barad’s notion of diffractive reading, proposing a new methodology in Human-Computer Interaction (HCI) called Diffractive Methodology (DM). This approach offers a nuanced and exploratory evaluation, focusing on differences across participant experiences and tracing the potential sources of these differences to produce deeper insight. The study found that participants used the AI system in two main ways: for creative ideation and for creative production. The analysis revealed that AI for ideation requires a degree of machine agency, while AI for production requires greater human control. The study also highlights the ethical concerns surrounding the use of AI in creative practices, including issues of authorship, plagiarism, and the potential for AI to undermine the originality of human-created works. The paper concludes that generative AI has the potential to augment human creativity, but its development and implementation must be guided by ethical considerations. The study emphasizes the importance of developing clear and rigorous guidelines for the building and implementation of generative AI technologies, as well as the need for further research into the ethical implications of AI in creative practices.This paper presents a diffractive analysis of prompt-based generative AI, exploring its potential role in artists' creative practice. Seven visual artists were given access to a personalized instance of Stable Diffusion, fine-tuned on their own artwork. The analysis identified two dominant modes of use: AI for ideation and AI for production. The study highlights the ethical design considerations for the future development of generative AI interfaces. The paper discusses the ethical and moral dilemmas raised by Text-to-Image (TTI) systems, including issues of copyright, plagiarism, artistic merit, and economic implications. It also examines the impact of AI on the role of the human creator and broader cultural implications. The study emphasizes the importance of developing clear and rigorous guidelines for the building and implementation of generative AI technologies. The paper draws inspiration from Karen Barad’s notion of diffractive reading, proposing a new methodology in Human-Computer Interaction (HCI) called Diffractive Methodology (DM). This approach offers a nuanced and exploratory evaluation, focusing on differences across participant experiences and tracing the potential sources of these differences to produce deeper insight. The study found that participants used the AI system in two main ways: for creative ideation and for creative production. The analysis revealed that AI for ideation requires a degree of machine agency, while AI for production requires greater human control. The study also highlights the ethical concerns surrounding the use of AI in creative practices, including issues of authorship, plagiarism, and the potential for AI to undermine the originality of human-created works. The paper concludes that generative AI has the potential to augment human creativity, but its development and implementation must be guided by ethical considerations. The study emphasizes the importance of developing clear and rigorous guidelines for the building and implementation of generative AI technologies, as well as the need for further research into the ethical implications of AI in creative practices.