From Creation to Curriculum: Examining the role of generative AI in Arts Universities
Atticus Sims
TL;DR
The paper argues that generative AI, especially diffusion-based image models like Stable Diffusion, demands a recalibration of arts education. It maps the tool landscape, emphasizing open-source ecosystems, core mechanisms (diffusion, CLIP, latent diffusion), and practical components (checkpoints, seeds, prompts, ControlNet, LoRA, textual inversions) for educational use. Through July 2023 workshops and an exhibition, it demonstrates a constructionist, learning-by-doing approach that situates students in authentic, collaborative, and iterative creative practice, supported by cloud-based workflows and low-code interfaces. The study highlights the educational benefits, challenges (technical setup, cloud compute limits), and strategies for scaling teacher facilitation, with a strong call for rapid adoption to prepare students for AI-augmented art professions. Practically, the work provides a blueprint for curricular integration, teacher guidance, and community-building to sustain AI-enabled creativity in arts universities.
Abstract
The age of Artificial Intelligence (AI) is marked by its transformative "generative" capabilities, distinguishing it from prior iterations. This burgeoning characteristic of AI has enabled it to produce new and original content, inherently showcasing its creative prowess. This shift challenges and requires a recalibration in the realm of arts education, urging a departure from established pedagogies centered on human-driven image creation. The paper meticulously addresses the integration of AI tools, with a spotlight on Stable Diffusion (SD), into university arts curricula. Drawing from practical insights gathered from workshops conducted in July 2023, which culminated in an exhibition of AI-driven artworks, the paper aims to provide a roadmap for seamlessly infusing these tools into academic settings. Given their recent emergence, the paper delves into a comprehensive overview of such tools, emphasizing the intricate dance between artists, developers, and researchers in the open-source AI art world. This discourse extends to the challenges and imperatives faced by educational institutions. It presents a compelling case for the swift adoption of these avant-garde tools, underscoring the paramount importance of equipping students with the competencies required to thrive in an AI-augmented artistic landscape.