The unfortunate reality is that wars and political and economic instability in different parts of the world has meant there has always been refugees – individuals and families who decide to risk everything to reach and make a life in a new place. Or, as is far too often the case, simply get away from wherever they are, to anywhere else, to save their lives.
However, the numbers of refugees around the world has reached new highs. The UN Refugee Agency reports that in 2018:
“We are now witnessing the highest levels of displacement on record.
An unprecedented 68.5 million people around the world have been forced from home”.
“Among them are nearly 25.4 million refugees, over half of whom are under the age of 18”.
“There are also an estimated 10 million stateless people who have been denied a nationality and access to basic rights such as education, healthcare, employment and freedom of movement”.
Devastation of swathes of the Middle East in recent years has created a near overwhelming refugee problem. Of the 25.4 million refugees worldwide, 6.3 million come from Syria. Afghanistan has contributed 2.6 million and South Sudan 2.4 million – the three countries together accounting for 57% of the total.
Successfully re-homing as many of these refugees as possible, as quickly as possible, is one of the greatest challenges facing the world today. And new technology is being brought into play to help. One particular example is ‘Annie’, an algorithm named after Annie Moore, the Irishwoman who was the first to officially pass through Ellis Island off the coast of New York, when it was the gateway to the millions of immigrants arriving in the USA.
‘Annie’ is a matching algorithm that is being used in the United States to help pair refugees to the country with the location that will give them the best chance of flourishing in their new lives in a strange land far from home. Annie is based on a machine learning process that feeds the algorithm with huge volumes of data from historical records on past refugee placements.
It looks at factors such as age, education, professional experience, language and religion. Based on current opportunities and constraints and previous outcomes for past refugees that are a close match to those currently being relocated, Annie then suggests a short list of the best possible destinations.
Until now, organisations and authorities making relocation calls based choices on little more than local capacity with little to no regard to matching locales with the individual characteristics of refugees. The approach now being used is not a revolutionary one. It’s been used in commercial applications such as matchmaking and dating sites and demonstrated its effectiveness. However, in its new application the results could be revolutionary. Using algorithms such as Annie, there are now other similar solutions elsewhere in the world with Switzerland one example.
It is still too early to say what the real impact of using big data algorithms in the rehoming of refugees will be. But it is hoped that taking into consideration the specifics of refugees themselves and the communities that have the capacity to offer them a new place to live will result in better outcomes for both sides of the equation.