Thursday, November 10, 2016

Using Big Data to Find Undocumented Immigrants

President-elect Trump
The deportation of millions of undocumented immigrants here in the United States appears to be a priority for President-elect Trump.

Critics, however, point out that the cost alone will be a prohibitive factor in tracking down millions of immigrants, many of whom have continued to remain in the United States after their Visa's expired or who managed to cross the border undetected.

While it is true that the government will have to hire thousands of new federal immigration agents to carry out the deportations, identifying and locating undocumented persons may not be as difficult or costly as one might think.

In fact "big data" could play a key role in both identifying and locating undocumented immigrants through the use of highly sophisticated computer programs capable of performing multiple in-depth background checks on every man, woman, and child living in America today, with the sole purpose of determining who should, and who should not be here.

Using a process of elimination, supercomputers would be capable of identifying and determining the status of all US  residents by accessing both public record and non-public record data held on them. This includes birth and naturalization certificates, drivers license records, education, employment, credit history, property ownership along with many other data points.

Consequently, if someone is unlawfully working in America today (even paying taxes) using a fake or stolen Social Security number, they would almost certainly be identified. Further, if someone rents a home and has opened up accounts with local utility companies under a false name or stolen identity, they too would be identified.

In fact, anyone whose data (or lack of data) falls into the category of suspicious is likely to find themselves the subject of scrutiny or even possibly a criminal investigation.

Of course, while supercomputers can search and locate information on people, it still requires a living person to analyze the data and physically locate them.  That can be expensive!


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