AI Art and the Sociotechnical Interactions with Artists: Implementing AI Algorithms to Generate Self-learning Art Styles

Lee, Caleb, School of Engineering and Applied Science, University of Virginia
Behl, Madhur, EN-Comp Science Dept, University of Virginia

The general problem relates to the relationship between AI Art and traditional artists. More specifically, the debate stems from the argument that the methods of data acquisition for AI infringe on fair use copyright laws meant to protect artists, and that said infringement could potentially endanger the lives of creators on a global scale on an irreparable level. Both the STS and technical problem aim to look for alternative arguments and solutions, where there could be safe alternatives for AI to be incorporated into the art process rather than being excluded altogether; The technical problem proposes an alternative approach to conventional AI art by eliminating the need for external data, while the STS problem encompasses the actor-network theory framework of artists by taking apart the roles of both the artist and AI while analyzing the various lens the arguments are scrutinized under.

BS (Bachelor of Science)
AI, Art, Machine Learning

School of Engineering and Applied Science

Bachelor of Science in Computer Science

Technical Advisor: Briana Morrison

STS Advisor: Caitlin Wylie

Technical Team Members: N/A

Issued Date: