Evaluating Glaze's Effectiveness: A Critical Analysis of AI Art Protection Through Non-Artist Perspectives and Common Image Transformations

This paper presents a systematic evaluation of Glaze 2.1, a tool designed to protect artists' styles from AI mimicry. We examine its effectiveness against common image transformations typically applied by social media platforms and assess its protection capabilities through the perspective of non-artist users. Our methodology combines technical analysis of how transformations like JPEG compression, scaling, blurring, and sharpening affect Glaze's protective perturbations with a comprehensive user study involving participants without specific artistic expertise. Results indicate that Glaze exhibits significant vulnerabilities when protected images undergo standard social media processing, with certain transformations substantially reducing its effectiveness. These findings highlight the challenges in developing robust protection mechanisms that can withstand real-world usage scenarios while remaining practical for artists. We contribute valuable insights into the limitations of current AI art protection tools and suggest directions for developing more resilient solutions that can better safeguard artists' intellectual property in digital environments.

Authors

Publication Details

Journal
AHFE international
Published
2025-01-01
DOI
https://doi.org/10.54941/ahfe1006086
Primary Topic
Digital Media and Visual Art
Type
article
Field-Weighted Citation Impact
0.00
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article

Evaluating Glaze's Effectiveness: A Critical Analysis of AI Art Protection Through Non-Artist Perspectives and Common Image Transformations

Rashit Nasyrov, Pascal Laube, John-Paul Bach
AHFE international
Digital Media and Visual Art
article

Evaluating Glaze's Effectiveness: A Critical Analysis of AI Art Protection Through Non-Artist Perspectives and Common Image Transformations

Rashit Nasyrov, Pascal Laube, John-Paul Bach
article en

Abstract

This paper presents a systematic evaluation of Glaze 2.1, a tool designed to protect artists' styles from AI mimicry. We examine its effectiveness against common image transformations typically applied by social media platforms and assess its protection capabilities through the perspective of non-artist users. Our methodology combines technical analysis of how transformations like JPEG compression, scaling, blurring, and sharpening affect Glaze's protective perturbations with a comprehensive user study involving participants without specific artistic expertise. Results indicate that Glaze exhibits significant vulnerabilities when protected images undergo standard social media processing, with certain transformations substantially reducing its effectiveness. These findings highlight the challenges in developing robust protection mechanisms that can withstand real-world usage scenarios while remaining practical for artists. We contribute valuable insights into the limitations of current AI art protection tools and suggest directions for developing more resilient solutions that can better safeguard artists' intellectual property in digital environments.

AHFE internationalVol. 165
Openalex Percentile: Top 73%
Digital Media and Visual Art
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