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The AC Digs Into: Potential Revenue of Cultural Racketeering

July 17, 2019

Fiona Greenland Interview

As one of their most recent accomplishments, the MANTIS project published the article “A Site-Level Market Model of the Antiquities Trade.” This cutting-edge research focused on two sites in Syria and was able to quantify the potential loss to looting based on archaeological records and market value. This research is important because it fills a critical gap in numerical data about looting in the Middle East.

The MANTIS project (Modeling the Antiquities Trade in Iraq and Syria) is made up of an interdisciplinary research team at the University of Chicago working at the interface of economics and archaeology. Their work combines satellite images, archaeological records such as excavation reports, and market data to undertake rigorous investigations of patterns of looting, trafficking, and cultural violence in Iraq and Syria. The Antiquities Coalition is happy to continue supporting this important work. 

We spoke to Fiona Greenland, the Principal Investigator at MANTIS, to learn more about their recent publication.

Why did you help found the MANTIS project initially?

My collaborators and I were convinced that many of the big, unanswered questions about antiquities looting and trafficking – What’s it all worth? What is being stolen? Where are things going? – could be better answered through systematic study of empirical data. We got started in 2015 when ISIS was making global headlines by looting and destroying archaeological materials, but our research questions have always extended beyond any single insurgent group.

What is the main point you would want our readers to take away from MANTIS’ conclusions in the article “A Site-Level Market Model of the Antiquities Trade”?

That there is a market for anything archaeological. We assessed just a portion of each site – about 10% of Tell Bi’a and 40% of Dura Europos – and estimated their overall market values at $3 million and $18 million, respectively. Syria has over a thousand archaeological sites. The potential revenue for black marketeers is enormous.

In the article, you study two sites in Syria. How and why did you choose Tell Bi’a and Dura Europos?

We selected Tell Bi’a and Dura Europos for three reasons. First, taken together, they span key periods of past inhabitation in the region: Bronze Age, Hellenistic, and Roman. Second, we needed sites that had comprehensive excavation records so that we could build our database of artifacts. Finally, we knew that both sites had been looted during the Syrian civil war, such that our monetary estimates were representative of the kinds of objects that may have been stolen and trafficked.

What was most surprising about your research?

How difficult it was! We had to figure out how to get the excavation data and online vendor records to “talk” to each other in the machine learning model. This was a novel approach, and it required a couple of years’ worth of experimentation, practice, and refinement before we were completely confident in the results. We were committed to the full process of systematic, experimental work, which included having our model checked and validated by several top-notch scholars of the antiquities market and through blind peer review. Passing their litmus test was our gold standard. Otherwise, what would be the point? The last thing we wanted was to offer up an estimate that would wither under scrutiny.

Why are more accurate estimates of economic losses important to countering the destruction and illicit trade of antiquities?

Putting things in dollar terms, for better or for worse, gets people’s attention. It makes the problem relatable and convincing to folks who may not otherwise spend much time thinking about archaeological materials as cultural heritage, or as scientific and historical data. Up to this point, estimates of economic losses due to looting had been limited to small samples from auction catalogs or interviews with local people. That earlier work is important, but their estimates were not testable nor  replicable. They also could not scale up to the level of dig site or region, which is important since illegal trade networks span transnational regions all the time.

Did you find any information about how the economic losses impacted local populations?

We didn’t study that question. It’s an important one, though. A more comprehensive examination of the economic and social forces that link healthy, protected archaeological sites with local communities would be necessary to fully address that question.

Your work is unique in its use of machine-learning to study the illicit trade. What do you think the role of technology is in the study of illicit trade networks and the fight against cultural racketeering?

I see a big opportunity for machine-learning and artificial intelligence techniques to process large data scrapes from online antiquities vendors to look for inventory and purchase patterns. That could be a significant step in mapping the global market.

This article is an important step in assessing the illicit trade of antiquities. What are the necessary next steps?

There is always more work to be done, and the good news is that there are parallel efforts to study and dismantle this trade in universities and cultural heritage organizations in the Middle East, Europe, and North America. One next step I’d like to see is the replication of our model on other sites, preferably outside of Syria, to make estimate comparisons on really different sorts of objects. This would enable us to chart relative values across the antiquities trade. Another step is to go back to the Syrian case and use interdiction reports, police records, and captured insurgent documents to figure out where those conflict zone artifacts ended up. That’s the million-dollar question.