Data Mining and the US Government
On the morning of September 11, 2001, millions of Americans, and many more around the world, woke up to heart-wrenching news of a horrific magnitude. Two planes had collided into the twin towers of the World Trade Center in New York, a third rammed into the Pentagon in Washington, D.C., and yet a fourth crash-landed in Philadelphia. All victims of this carefully planned act of terrorism, several hundreds of innocent lives were lost in the direct assaults on the planes, a couple of thousand more were injured or killed from the damage caused by the attacks, and hundreds more were sacrificed in the rescue attempts. It is unthinkable that such a large scale operation could have been crafted. More unbelievable is that the attackers were able to execute their plans. After all, the third plane, though it did not hit its mark directly, managed to cause a great deal of damage to the Pentagon, the symbol of national security of the United States
Soon after, reports stating that the events of 9-11 could have been prevented, if proper action been taken given the information available, began surfacing. The American public began questioning the government's usage of the intelligence gathered, particularly the vast amount of intelligence that was collected electronically. Could proper technology, like data mining, have been utilized more effectively to notify authorities of the terrorists' suspicious activities? Given the nature of data mining, would its usage be justified at the cost of personal privacy to the general public? This paper aims to survey the usage of data mining technology as a tool to gather information and look for suspicious behavior, and to discuss the ethical implications to privacy of this technology. Is it possible to preserve national security while also protect personal privacy, or will one need to be compromised for the other?
What is Data Mining?
Data mining is essentially the ability to discover new information by exploring through various databases of existing information. According to Laura and Jack Cook, data mining "facilitates the discovery of previously unknown relationships among the data. …These operations present results that users already intuitively knew existed in the database." As an example, let us take a school system consisting of three databases: one which stores the student profiles consisting of name and identification number, another to store student grades based on identification number, and the last one stores all the transactions at the bookstore through the student identification card. This is a simple example, but it should illustrate our point. Alone, the separate databases might not tell us much. With data mining techniques, the process might be able to tell us that in a particular school year, students of a certain ethnic background obtained above a 3.0 GPA, or that the bookstore sold mostly engineering books to students last year, or...