Who, or Rather, What Painted This? Generation Z's Attitudes Towards Artificial Intelligence Artworks

Authors

  • Juliette Park North Creek High School
  • Rhonda McGee North Creek High School

DOI:

https://doi.org/10.47611/jsrhs.v12i4.5804

Keywords:

Artificial Intelligence, AI art, Generation Z, Gen Z, Artworks, Paintings, Gen Z Attitudes

Abstract

Throughout art history, the exact boundaries of what can and cannot be considered art has long been debated, and the rise of artificial intelligence (AI) algorithms that produce artworks has rekindled this debate in the context of technology. History indicates that the answer to what is considered “art” largely depends on the evaluator’s personal definition of creativity and their perception of the artist, which gives reason to investigate people’s attitudes towards AI art. Pre-existing research has discovered a negative perception bias towards AI artists in adult generations. However, no studies have been conducted on Generation Z specifically. Gen Z possesses a close association to technology which distinguishes them from previous generations, and could therefore produce differing attitudes towards AI art. Therefore, this study seeks to investigate: what are Generation Z’s attitudes towards AI art? This study defined “attitudes” to combine attitudes towards the artist, and attitudes towards the artworks. Therefore, a mixed method study consisting of 1) a ratings test to examine any perception biases towards AI artists, and 2) a questionnaire to investigate the criteria Gen Z used to determine value in AI artworks were combined to answer this question. It was concluded that Generation Z had a neutral attitude towards AI artists and responded rather well to AI art styles of landscape paintings.

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Published

11-30-2023

How to Cite

Park, J., & McGee, R. (2023). Who, or Rather, What Painted This? Generation Z’s Attitudes Towards Artificial Intelligence Artworks. Journal of Student Research, 12(4). https://doi.org/10.47611/jsrhs.v12i4.5804

Issue

Section

AP Capstone™ Research