The following excerpt is from an article in the New York Times by Zach Zorich. The full article, entitled “How Archaeologists Are Using Deep Learning to Dig Deeper: Trawling ancient history with neural nets,” is available online.
Shawn Graham, a professor of digital humanities at Carleton University in Ottawa, uses a convolutional neural network called Inception 3.0, designed by Google, to search the internet for images related to the buying and selling of human bones. The United States and many other countries have laws requiring that human bones held in museum collections be returned to their descendants. But there are also bones being held by people who have skirted these laws. Dr. Graham said he had even seen online videos of people digging up graves to feed this market.
“These folks who are being bought and sold never consented to this,” Dr. Graham said. “This does continued violence to the communities from which these ancestors have been removed. As archaeologists, we should be trying to stop this.”
He made some alterations to Inception 3.0 so that it could recognize photographs of human bones. The system had already been trained to recognize objects in millions of photographs, but none of those objects were bones; he has since trained his version on more than 80,000 images of human bones. He is now working with a group called Countering Crime Online, which is using neural networks to track down images related to the illegal ivory trade and sex trafficking.