Researchers are using artificial intelligence to solve an art history mystery by analyzing paintings and identifying patterns humans might miss. The BBC's Harriet Bradshaw reports on how machine learning algorithms examine brushstrokes, composition, color palettes, and other visual elements to help attribute works to specific artists or time periods.
AI systems trained on verified artworks can compare unknown or disputed pieces against vast databases, flagging similarities that support or challenge existing theories about origin and authorship. The technology proves particularly useful for authentication disputes and for studying artistic evolution across centuries.
Art historians emphasize that AI serves as a research tool rather than a replacement for expert judgment. The algorithms highlight connections and anomalies that curators and scholars then investigate further using traditional methods like pigment analysis and historical documentation.
The approach reflects a broader trend of AI moving beyond tech and finance into cultural institutions. Museums and galleries have begun deploying these systems to catalog collections, detect forgeries, and answer longstanding questions about provenance that have puzzled experts for decades.