Explore how persistent homology from algebraic topology provides objective mathematical tools for analyzing artistic styles in this 13-minute conference talk. Learn how topological data analysis can statistically differentiate between artists from various artistic movements and even distinguish between authentic artworks and AI-generated images created in specific artists' styles. Discover how mathematical frameworks can offer interpretable insights into the deeply personal and expressive nature of art, moving beyond subjective definitions of artistic "style" and "current" to provide quantitative analysis of visual artistic elements.