In the late 2010’s, investigative journalism and a series of NGO reports shone a spotlight on tragedies involving forced labor in the global fishing fleet. This revelation received considerable media coverage and brought into question the role of forced labor in seafood imported to the US, culminating in a law (the Trade Facilitation and Trade Enforcement Act) signed by President Obama in 2016 banning the import of seafood produced by enslaved people. While forced labor in the world’s fishing fleet has been widely documented, the question remains what the extent of forced labor at sea is and what fisheries it affects.
We estimated the extent of forced labor in the global fishing fleet by examining the behavior of fishing vessels, working with the hypothesis that ships using forced labor behave in an observably different manner than those that do not. By combining satellite data from Global Fishing Watch, expertise from human rights practitioners, and machine learning techniques, we built an algorithm that can identify fishing vessels with suspected forced labor on board.