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All the rage for the better part of the recent decade, predictive analytics are now used in a wide range of fields: predicting which students are in danger of dropping out of a university, helping Los Angeles social workers find possible cases of fraud, and shaving millions of unnecessary miles per year off UPS drivers’ routes. Data from the past helps the algorithms anticipate problems before they arise.
When it comes to refugees, a lack of forethought has made an already unstable geopolitical situation even worse. Few host countries had the ability to absorb refugees, and nobody fully anticipated the challenges the front-line states of Jordan, Lebanon, Turkey, and Greece would face as temporary homes for thousands fleeing to Europe. When many European states stopped accepting migrants, that only exacerbated the strain on front-line states.
Meanwhile, even willing countries like Germany left thousands stuck in refugee camps far longer than anyone thought would be required.
Migration data is already being collected by a variety of sources, including national population censuses, sample surveys, smartphones, border crossings and administrative sources like population registers.
Such rolling data could be a game-changer for officials on the front lines of the crisis. Sophisticated analytics could help experts confidently chart where refugees are likely to head next. Policymakers, spotting signs of a future influx, might reroute refugees to different countries. This real-time data could also help organizations quickly and accurately shunt money and goods to the locales that need them the most.
Read the full article about how big data could help refugees by Anirudh V.S. Ruhil at The Conversation (via Mashable).