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The Sciences

Slavery from Space: Citizen Science in the Antislavery Movement

Citizen Science Salon iconCitizen Science SalonBy GuestApr 6, 2019 1:10 PM

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Slavery from Space is a citizen science project that allows users to further the antislavery movement by mapping the locations of activities in which people are frequently found to be enslaved. How many slaves do you think there are in the world? You might be surprised. In 2016, the International Labour Organization estimated that 40.3 million people were enslaved globally, of which 28.7 million are women and girls and 24.9 million are in forced labor. To put those numbers into perspective, those sums are roughly equivalent to the populations of California, Texas, and Australia, respectively. These numbers are as important as they are difficult to estimate: the success of antislavery efforts depends on knowing how many slaves there are and where they are. Despite these challenges, the UN’s Sustainable Development Goal 8.7, adopted in 2015, demands an end to modern slavery by 2030. I work at the Rights Lab at the University of Nottingham, which brings together a diverse group of researchers to tackle this global challenge. A key focus of the Rights Lab is the development of robust measurement and analysis of the prevalence and location of slavery, the goal of which is to underpin the credibility, confidence, and effective action of the antislavery movement. Prevalence and location data will allow governments to design and resource appropriate policy responses, such as the Indian government’s 2016 commitment to free 18 million bonded workers by 2030, as well as allow NGOs to plan more effective interventions on the ground. The Rights Lab’s “Slavery from Space” initiative is the world’s first use of data captured by satellites to map and measure slavery, using both new machine learning techniques and citizen science methods (Boyd et al, 2018; Foody et al, 2019). The team has uncovered sites and industries with high levels of slavery thanks to satellites continually capturing data in all corners of the Earth.

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