Not long after Marcus is released, he was followed by two police officers and was arrested for taking unusual trips at unusual times using the BART.  Because Marcus’s fast pass was able to collect data on where and when he took trips, a computer algorithm incorrectly marked him down as a possible criminal. When he was brought home in handcuffs his parents talked the police out of incarcerating him. Following these events, Marcus and his father argued on the role of data mining algorithms. Marcus believed that the police are ineffective to deal with the ‘haystack’ of data that data mining algorithms sifted through. On the other hand, his father believed that it was beneficial to have data samples of everyone so that abnormal patterns could be detected and questioned.

Taking a stance on data mining and its accompanying algorithms is not easy. Depending on the context, my view would relate closer to Marcus’s side or his father’s. One example that has been brought up in our class was when our credit card companies freeze our accounts. On an international trip, a few expense will trigger the computer algorithm to freeze the account. These algorithms are in place to compare your expenditures with your previous patterns of spending. This system is in place to protect the user from fraud, and it is beneficial because it causes very little inconvenience to the user. Another example of data mining is how companies use their customers’ data to develop custom marketing strategies. Companies want to be successful and to do this, they wish to brand their product to any type of consumer. This might be seen as a benefit to companies but it does infringe on the public’s privacy. The controversial aspect is how specific companies choose to survey people, Google for example is though to have used ambient sound from their users to generate ads.

There are not many inconveniences of data mining, the important matter is the level of privacy that the data contains. Sensitive data is not usually used in these data mining algorithms and the data mining framed in the book is a exaggeration of what could possibly happen if surveillance extends too far. The systems we have in place now and are currently being developed are assets rather than obstacles.