NEW TECHNOLOGY IS making advocates and law enforcement optimistic that they might finally have a chance at freeing men held captive at sea on large commercial fishing vessels.
The men [and it is almost always men] who get forced into slavery aboard those ships have often gone willingly, seeking work, says Val Farabee, director of research at Liberty Shared, an organisation that fights human trafficking. But once isolated at sea, their wages are withheld and they’re subjected to violent, bleak working conditions for years.
Forced labour and slavery are terms used interchangeably by human trafficking experts to refer to people working against their will. Though well documented in ships that fish illegally, the fishing industries’ dizzying network of enforcement and regulation, as well as the vastness of the oceans, make it difficult for law enforcement to help those trapped on such ships.
It’s unclear how many people are held on fishing boats, but an estimated 21 million people are trapped in enslaved labour around the world, according to the International Labour Organization.
Fighting crime from space
“As global fish stocks are declining these commercial fishers are having to travel farther,” says Oceana analyst and illegal fishing expert Lacey Malarky. “It’s resulting in operators resorting to IUU (illegal, unreported, and unregulated) fishing and human rights abuses to protect costs.”
Malarky recently worked with Farabee to publish a report that demonstrates how trends in satellite data may indicate a vessel is fishing illegally and harbouring slaves.
Liberty Shared logs fishing vessels accused and convicted of using slave labour.
Malarky then monitored those vessels on Global Fishing Watch, an online database that tracks fishing ships via their Automatic Identification System (AIS), an onboard satellite transmitter. AIS was developed to prevent ship collisions, but by creating a virtual log of how and when ships move, analysts are able to develop algorithms that use ship speed and direction to detect when a ship might be fishing.
“We noticed that vessels engaged in illegal behaviour behave differently,” says Farabee.
Four key behaviours tipped them off. Vessels that stayed at sea for months on end elicited concern for how long the crew had been forced to work.
Other ships temporarily turned off their AIS signal; data showed several ships turning off AIS as they entered marine protected areas and turning it back on as they exited. Though some fishers claim to turn their AIS off to avoid dangers like piracy, their proximity to protected waters sends up a red flag.
Another suspicious behaviour is known as trans-shipment, when a refrigerated cargo vessel meets up with a fishing vessel to offload catch and take it to shore. The activity, though often practiced legally, allows ships to remain at sea for longer and makes it more difficult to trace a fish’s origin.
Finally, ships that avoided ports where laws are strictly enforced indicated to the researchers that they might have something to hide. One company could register different vessels in its fleet under different countries. When that happens, it becomes the vessels’ “flag state,” but vessels that engage in illegal activity have been known to register under flag states where enforcement is weak.
Based on those criteria, Malarky zeroed in on three vessels flying under South Korean, Taiwanese, and Moldovan flags. The last vessel changed flags from Honduras to Bolivia before registering under Moldova.
While the satellite data from each of the vessels indicates suspicious activity, Malarky and Farabee note that human intervention is required to confirm whether the crew is forced into labour, but identifying suspicious helps law enforcement know where to start.
Farabee is working with researchers from the University of California at Santa Barbara to identify more patterns that can identify ships with slaves on board.
“Whether that behaviour is illegal fishing, wildlife tracking, or forced labour is unclear, but that’s what we’re trying to tease out,” she says.
Acting on data
“[The data] can highlight something that merits inspection,” says Peter Horn, the project director of Pew’s Ending Illegal Fishing Project.
“One of the challenges is having people able to identify these conditions,” says Horn. “Thailand has good laws, but they didn’t identify many indications of forced labour.”
Last year, Human Rights Watch published a report outlining how the Thai government systematically failed to identify slave labour on fishing ships.
Horn says boat inspectors need special training to spot forced labour. They might, for instance, ask a ship’s crew about working conditions in the presence of the ship’s captain. Under the watchful eyes of those who enslaved them, crew members are unlikely to speak out, Horn says.
In 2015, the Associated Press investigated the supply chains travelled by slave-caught fish. Their investigation showed that the illegal fish ended up in common American grocery stores like Kroger, Albertsons, Safeway, and Walmart. Illegal fishing itself is thought to generate more than US$23 billion each year.
To help prevent consumers from financing slave labour aboard fishing ships, the Monterey Bay Aquarium added a Seafood Slavery Risk Tool to its Seafood Watch program. Earlier iterations of the program helped consumers avoid fish that came from unsustainable fisheries.
The aquarium’s database allows users to search by country or fishery for suspicious behaviour. Skipjack tuna caught in Taiwan is shown as highly likely to use slave labour.
Malarky, Farabee, and Horton are all optimistic that globally tracking ships and using machine learning to identify suspicious behaviour can help bring justice to those forced into slavery.
Simply put, Malarky says, “it’s a game changer.”
Lead Image: A Taiwanese-flagged fishing vessel suspected of illegal fishing activity moves through the water off the coast of Fre.
PHOTOGRAPH BY XM COLLECTION, ALAMY STOCK PHOTO