Date of Award
Spring 5-10-2024
Document Type
Thesis (Master's)
Department or Program
Computer Science
First Advisor
Michael A. Casey
Second Advisor
Lorie Loeb
Third Advisor
Elizabeth L. Murnane
Abstract
This thesis investigates the shifting boundaries of art in the era of Generative AI, critically examining the essence of art and the legitimacy of AI-generated works. Despite significant advancements in the quality and accessibility of art through generative AI, such creations frequently encounter skepticism regarding their status as authentic art. To address this skepticism, the study explores the role of creative agency in various generative AI workflows and introduces an "artist-in-the-loop" system tailored for image generation models like Stable Diffusion. This system aims to deepen the artist's engagement and understanding of the creative process. Additionally, a novel tool, the Latent Auto-recursive Composition Engine (LACE), which integrates Photoshop and ControlNet with Stable Diffusion, is introduced to improve transparency and control. This approach not only broadens the scope of computational creativity but also enhances artists' ownership of AI-generated art, bridging the divide between AI-driven and traditional human artistry in the digital landscape.
Recommended Citation
Huang, Yenkai, "Latent Auto-recursive Composition Engine" (2024). Dartmouth College Master’s Theses. 131.
https://digitalcommons.dartmouth.edu/masters_theses/131