CP: We are indeed aware of all of the legal issues which can potentially emerge. We also know that some art experts seem to move away from “authentication” for the reasons you mention. Yet because of the (occasionally) hostile view towards authentication, I think it is even more important to have at hand a tool which is completely objective, emotionless, and has no fear of lawsuits.

While we are continuously working on improving the accuracy, it is well known that, by its nature, no AI algorithm can be 100% certain. We ensure our clients that the analysis is done most carefully and with due diligence, but we also explain to them that we cannot provide 100% accuracy. The clients have, of course, the freedom to use the authenticity evaluation resulting from an algorithm in any way they find meaningful for their purpose, but we exclude all warranty on any further use of the technical report we provide to them.

JB: Many technical folks I have spoken to are suspicious that machine learning can correctly detect forgery based on images alone. You yourself have a Ph.D. in particle physics and your co-founder Christiane Hoppe has an advanced degree in mathematics. What are these other folks missing that the two of you see in the potential for this solution/approach?

CP: It would be interesting to know why are those folks suspicious. In any case, teaching computers how to model large amounts of data in a meaningful way is nowadays a global trend reaching out to all domains, and I don’t see why art — or art authentication, for that matter — should be an exception. When developing an algorithm for a problem which is a rather atypical, one should, of course, take into consideration the particularities of that problem. To give you an example, when preprocessing the images, we are careful to not cut them into patches smaller than the brushstroke and we make sure to remove effects such as light spots, shadows, etc. Our network architecture is also specifically designed for this type of image recognition. So I wouldn’t say that there is a big secret that people out there are missing, but rather many small details which should be embedded at every step of analysis in order to have it working properly.

Finally, the results alone should speak for themselves, as in all tests, the algorithm worked perfectly well.

JB: What is the long-term vision for Art Recognition?

CP: Our vision is that Art Recognition will become a trusted label and that every artwork coming up on sale has been checked by our algorithm.

JB: Why have you decided to partner up with Artnome?

CP: We are really thrilled to see that you are so enthusiastic about the same topics as we are, and it is great fun to team up and move the case forward together. Your network and images are a tremendous help for us. At the same time, we hope we can help you fulfill one of your dreams – bringing down forgery in the art market!

JB: How do people engage with you if they want to know if they have a forgery or an authentic work?

CP: For the time being, they can send us an e-mail with a photo of the artwork in question and their assumption on the artist. Our algorithm then analyzes the image, and within few days, we get back to them with a full report. We are planning to soon give the possibility to our clients to upload the images directly via our website.

Conclusion

We need to stop celebrating forgers as lovable rascals getting one over on rich collectors and start celebrating real heroes like the Art Recognition founders, Popovici and Hoppe-Oehl. The reality is that art forgers undercut our shared humanity by compromising the historical record of our most important cultural objects: Our art. I’m proud and excited to be both a partner and an advisor to Art Authentication and look forward to working with them to put an end to forgery in our museums on the art market in my lifetime.