How to Catch a Criminal in the 21st Century and Why AI Might be Able to Help

By Shelby Jorgensen

There is a deep cultural fascination with art theft and forgeries – darlings of art crime. The classic image is that of a high-class, honorable thief in the night committing a heist worthy of Thomas Crown or the Ocean’s Eleven franchise. For forgers, Ken Perenyi and Elmyr de Hory have muddied enough waters to make it difficult to tell real from fake works, even for the best of experts. In either case, the investigator is often either a bumbling fool, allowing the thief to get away scot-free, or a seemingly omniscient Sherlock Holmes, hot on the trail.

In real life, art crimes are less glamorous and leave much greater wreckage in their wake, including tarnished reputations, heartbroken owners or decimated cultural heritage sites. The paths to recovering such pieces are numerous and multifaceted and at times protracted, particularly if the piece itself is ancient or has never before been cataloged, leading to a much more complicated and potentially mistaken provenance.^[1] As a way to combat these ongoing issues, databases became a popular way to try and retain information on stolen works, including ownership history, descriptions, frame information, and images.

Repatriation and restitution within international law are governed by a series of treaties with the most recent being created during the UNIDROIT Convention of 1995.^[2] This treaty specifically calls for a uniform law to be implemented for the return of stolen cultural heritage, but it remains unsigned by important countries such as the United States.^[3] Therefore, the 1970 UNESCO Convention remains the agreement primarily at play.^[4] Unlike the UNIDROIT document the UNESCO Convention doesn’t create a singular system that must be enforced, but instead looks to create a framework to help parties create legislation protecting cultural heritage.^[5] To read more about these conventions check out our Art Law Lunch Talk from 2020 “UNESCO Convention Turns 50”.