AI identified a masterpiece of the Renaissance. Art historians are skeptical.
It is not common for the work of authenticating art to make headlines in the media, but that is exactly what happened last year when a team of researchers in the UK determined that an anonymous, century-old painting known as the Tondo de Brécy was likely created by the Renaissance giant Raphael. It was a bold claim, with potentially enormous financial implications, but what truly captured people's attention was the technology researchers used to reach that conclusion: AI.
In recent years, the intersection between artificial intelligence (AI) and art has stirred the waters of the art world in previously unimaginable ways. What was once a sacred domain of art authentication has found itself amid this technological revolution, challenging not only the authority of art historians but also the very nature of how we understand and value art. The boldness of the claim was on par with the controversy that followed, particularly when another AI analysis conducted by the Swiss firm Art Recognition cast doubt on this attribution.
The original analysis, led by Christopher Brooke from the University of Nottingham and Hassan Ugail from the University of Bradford, used a facial recognition model to compare the Madonna in the Tondo de Brécy with Raphael's iconic Sistine Madonna. Their AI determined a 97 percent match, leading to the conclusion that both works were likely created by the same hand. This innovative use of AI in art authentication made headlines, and for a brief moment, it seemed that technology had triumphed in a domain traditionally governed by the trained eye of connoisseurs.
Dr. Christopher Brooke, honorary researcher at the University of Nottingham, is an expert in digital image analysis and co-author of the research paper.
"This study demonstrates the capabilities of machine learning to determine the likelihood that paintings by the 'old masters' are by the same artist. In this case study, the direct facial comparison yields a 97% match, a statistically very high probability that the artworks are by identical creators."
Dr. Christopher Brooke, honorary researcher
Professor Howell Edwards, honorary scientific advisor of the de Brécy Trust, stated: “Our previous Raman spectroscopic analyses of the pigments, which placed the Tondo painting firmly in the 16th-17th century and dispelled the idea that it was a Victorian copy, have been further vindicated by the facial recognition analysis of the Virgin and Child subjects and their great similarity to those of Raphael's Sistine Madonna.”
The Trust is absolutely delighted that this new scientific evidence confirms the attribution of the Tondo to Raphael, following the Raman spectroscopic analysis of its pigments carried out by Professor Howell Edwards, which confirmed its dating to the Renaissance period. It convincingly illustrates the increasing value of scientific evidence in the attribution of a painting.
Timothy Benoy, Honorary Secretary, of the deBrécy Trust
However, the celebration was short-lived. The Art Recognition model, which was trained with a mixture of authentic paintings and Raphael forgeries, later contradicted earlier findings, asserting with 85 percent certainty that the Tondo de Brécy was not the work of Raphael. Carina Popovici, founder of Art Recognition, defended her company's methodology, emphasizing the subtle differences in what each AI model was evaluating. This "battle of the AIs," as it was dubbed, became a microcosm of the broader debates surrounding the role of AI in art history.
This is not the first time AI has provoked such discussions. The influence of AI has been quietly growing in the art world, from curating exhibitions to identifying previously unattributed works. For example, AI has been employed to analyze brushwork in paintings by artists like Rembrandt, helping to authenticate works that were previously disputed. In 2018, researchers at Rutgers University used AI to study the painting styles of different artists, revealing previously unnoticed patterns and potentially reshaping our understanding of artistic evolution.
But as AI delves deeper into the art world, questions arise about the limits of technology in this deeply humanistic field. The debate revolves not only around whether AI can accurately authenticate art but also whether it can, or should, replace the critical judgment that has long been the foundation of art history. Scholars like Johanna Drucker and Claire Bishop have been vocal in their skepticism. In her 2013 paper, "Is There a 'Digital Art History'?", Drucker argued that while digital tools have made art history more accessible, they have not fundamentally altered its core methodologies. Bishop, in her essay "Against Digital Art History," expressed a similar sentiment, warning against reducing art to data points, a move she saw as symptomatic of a broader trend toward the metrication of knowledge.
These concerns are not without merit. The integration of AI into art history has led to a resurgence of formalism, a focus on the physical properties of artworks rather than their cultural context. Amanda Wasielewski, a professor of digital humanities at Uppsala University, warns that this approach could lead to a limited understanding of art, one that overlooks the rich theoretical frameworks developed over the past century. The AI's ability for "remote visualization," a method that analyzes vast amounts of visual data to identify patterns, is powerful but risks prioritizing the quantifiable over the qualitative.
However, despite these concerns, there is a growing acceptance of AI as a tool rather than a threat. Wasielewski herself acknowledges the practical benefits of AI in tasks such as file management and collection curation. These applications streamline the work of art historians and museum professionals without replacing their expertise. The real challenge, she suggests, is to ensure that these tools are used in ways that complement rather than eclipse traditional methods of historical art research.
The recent collaboration between Popovici and Nils Büttner, a German art history professor, is a good example. Despite their different approaches, Popovici's AI-driven analysis and Büttner's traditional methods reached similar conclusions about the attribution of a painting to Anthony van Dyck. Their partnership highlights the potential for AI and human expertise to coexist, each bringing their strengths to the table.
As AI continues to evolve, the dialogue between technologists and art historians will be crucial. These conversations will shape not only how we use AI in art but also how we define the role of technology in the humanities more broadly. While AI has undoubtedly left its mark on the canvas of art history, the brushstrokes of human interpretation and critical thinking remain essential to complete the picture.
KUADROS© creates replicas of paintings made with artificial intelligence produced by tools like Dalle, Midjourney, and Stable Diffusion.
