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How AI is Expanding Art History

Artificial intelligence (AI), machine learning, and computer vision are making significant strides in art history, challenging traditional approaches. Algorithms are now being employed to analyze brush strokes, color, and style, offering insights into artists' use of optics, recovering lost or hidden artworks, and even deciphering symbolic meanings. Despite the complexity of artworks and their nuanced human meanings, AI tools are proving valuable in automating analyses, processing subtle image details beyond human perception, and introducing new approaches to art scholarship.

Collaborations between computer scientists and art scholars are emerging, leading to early successes in "computer-assisted connoisseurship." AI methods are categorized into automating visual analyses, processing image subtleties, and introducing novel questions to art scholarship. For instance, AI can efficiently analyze poses in thousands of portraits, revealing trends across art movements. It can also extend perception by identifying lighting patterns in artworks, overcoming limitations in human visual perception.

Furthermore, advanced computer methods contribute to recovering lost cultural heritage, such as reconstructing missing parts of incomplete artworks or predicting probable colors of ghost paintings. For AI to fully empower art scholars, access to vast datasets and computing power is crucial, and efforts are underway to organize and make available extensive art-related information. The article suggests that future computational tools, utilizing high-resolution images, spectroscopy, chemical measurements, and linguistic data, could play a key role in recovering lost masterpieces and enriching our understanding of global cultural heritage. In essence, computation and AI appear poised to be the next transformative step in the ongoing intellectual adventure of understanding and interpreting our cultural legacy.

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