Date of Award
Spring 5-14-2024
Document Type
Thesis (Undergraduate)
Department
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, crit-
ically 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 var-
ious 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 Pho-
toshop 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: A Generative System for Creative Expression in Human-AI Collaboration" (2024). Computer Science Senior Theses. 50.
https://digitalcommons.dartmouth.edu/cs_senior_theses/50
Included in
Computer Sciences Commons, Graphic Design Commons, Illustration Commons, Interactive Arts Commons, Painting Commons