Human Intuition and Machine Generation: Exploring Emotional Authorship in AI-Assisted Design
Faculty Mentor
Travis Masingale
Presentation Type
Poster
Start Date
4-14-2026 11:30 AM
End Date
4-14-2026 1:30 PM
Location
PUB NCR
Primary Discipline of Presentation
Design
Abstract
This project explores how artificial intelligence influences emotional expression and visual decision-making in design, and where the boundaries between human intuition and machine generation begin to emerge. Through a series of visual case studies and a music perception experiment, the research investigates how emotional intention shifts when humans collaborate with AI tools. The visual experiments compare human-designed compositions with AI reinterpretations in order to observe how AI alters, reshapes, or amplifies emotional tone through aesthetic elements such as color, gradients, lighting, and visual atmosphere. By prompting AI systems to reinterpret human-created visuals, the project examines how machine-generated variations influence design decisions and emotional perception. In addition to visual exploration, a music listening test asks participants to distinguish between AI-generated and human-created songs. This experiment explores how audiences interpret emotional authenticity and whether listeners perceive differences in emotional depth between human and AI-generated media. Together, these experiments examine emotional authorship across three perspectives: human intention, machine interpretation, and audience perception. The findings suggest that meaning in AI-assisted design does not belong solely to the designer or the machine, but instead emerges through an iterative collaboration between human creativity, algorithmic generation, and the individuals experiencing the work.
Recommended Citation
Ramirez Castro, Ashley, "Human Intuition and Machine Generation: Exploring Emotional Authorship in AI-Assisted Design" (2026). 2026 Symposium. 9.
https://dc.ewu.edu/srcw_2026/ps_2026/p2_2026/9
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Human Intuition and Machine Generation: Exploring Emotional Authorship in AI-Assisted Design
PUB NCR
This project explores how artificial intelligence influences emotional expression and visual decision-making in design, and where the boundaries between human intuition and machine generation begin to emerge. Through a series of visual case studies and a music perception experiment, the research investigates how emotional intention shifts when humans collaborate with AI tools. The visual experiments compare human-designed compositions with AI reinterpretations in order to observe how AI alters, reshapes, or amplifies emotional tone through aesthetic elements such as color, gradients, lighting, and visual atmosphere. By prompting AI systems to reinterpret human-created visuals, the project examines how machine-generated variations influence design decisions and emotional perception. In addition to visual exploration, a music listening test asks participants to distinguish between AI-generated and human-created songs. This experiment explores how audiences interpret emotional authenticity and whether listeners perceive differences in emotional depth between human and AI-generated media. Together, these experiments examine emotional authorship across three perspectives: human intention, machine interpretation, and audience perception. The findings suggest that meaning in AI-assisted design does not belong solely to the designer or the machine, but instead emerges through an iterative collaboration between human creativity, algorithmic generation, and the individuals experiencing the work.
