This data will then be used to train machine learning algorithms to automatically recognise brick kilns in satellite imagery. If computers can pinpoint the location of such possible slavery sites, then the coordinates could be passed to local charities to investigate, says Kevin Bales, the project leader, at the University of Nottingham, UK.
South Asian brick kilns are notorious as modern-day slavery sites. There are an estimated 5 million people working in brick kilns in South Asia, and of those nearly 70 per cent are thought to be working there under duress – often to pay off financial debts.
Bales is hoping that his machine learning approach will produce a more accurate figure and help organisations on the ground know where to direct their anti-slavery efforts.
It’s great to have a tool for identifying possible forced labour sites, says Sasha Jesperson at St Mary’s University in London. But it is just a start – to really find out how many people are being enslaved in the brick kiln industry, investigators still need to visit every site and work out exactly what’s going on there, she says….
So far, volunteers have identified over 4000 potential slavery sites across 400 satellite images taken via Google Earth. Once these have been checked several times by volunteers, Bales plans to use these images to teach the machine learning algorithm what kilns look like, so that it can learn to recognise them in images automatically….(More)”.