As the world faces its largest crisis of displaced people since World War II, a new algorithm could help countries resettle refugees in a way that boosts their employment success and overall integration.
Researchers used a machine-learning algorithm to analyze historical data on refugee resettlement in the United States and Switzerland. They found that the refugees’ eventual economic self-sufficiency depended on a combination of their individual characteristics, such as education level and knowledge of English, and where they were resettled within the country. It turned out that refugees with particular backgrounds or skills achieved better outcomes in some locations than others.It could be just like the Cambodian refugees going to Georgetown outside D.C. in 1973:
The algorithm assigned placements for refugees that they project would increase their chances of finding employment by roughly 40 to 70 percent compared with how the refugees actually fared, according to the new study in Science.
“As one looks at the refugee crisis globally, it’s clear that it’s not going away any time soon and that we need research-based policies to navigate through it,” says Jeremy Weinstein, a professor of political science at Stanford University and a coauthor of the study. “Our hope is to generate a policy conversation about the processes governing the resettlement of refugees, not just on the national level in the United States but internationally as well.”
The group, from Stanford and ETH Zurich, says the algorithm, which could be implemented at virtually no cost, could help resource-constrained governments and resettlement agencies find the best places for refugees to relocate.
Where to go?
In recent years, a record number of people have been displaced as a result of war, persecution, and other human rights violations, surpassing the numbers seen after World War II. In 2016 alone, about 65.6 million people were forced to flee their homes, according to the United Nations’ refugee agency...MORE