First Advisor

Elisabeth Charman

Date of Award

5-22-2020

Document Type

Thesis

Degree Name

Bachelor of Science (B.S.) in Graphic Design and University Honors

Department

Art

Language

English

Subjects

Computer art, Art and computers, Artificial intelligence, Neural networks (Computer science), Graphic arts -- Technological innovations

DOI

10.15760/honors.903

Abstract

In this paper, I discuss the creation, execution and reception of my digital art series Fallen Objects, in which I collaborate with a neural net to create pseudo-found objects. I explore how artists might collaborate with Artificial Intelligence obliquely, not by having the AI generate the images themselves, but instead generate input for the artists to make the images. While many artists are focused on training neural nets to replicate their own art inputs, I instead focus on working with an AI trained on external, easily-accessible data and creating images from the prompts it delivers. In this way, the AI works not as the artist but as the muse, delivering inspiration instead of finished pieces. Additionally, the objects present a sort of reflected look of mankind’s collective psyche: the AI responds with things it feels are plausible from its training on human input, and by creating these objects, we can look into a sort of reflection of ourselves, as seen from a semi-objective third party.

Rights

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

Persistent Identifier

https://archives.pdx.edu/ds/psu/33153

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