Michael Morris makes the argument that, through mining student data, examining the digital footprints left by students in their day-to-day lives, universities could prevent violence from occurring on campus. This belief is founded on the idea that students intending to commit violence might leave some evidence of their bad intentions in their online actions. Morris rightly suggests that, if a student has shown strong negative opinions on a particular professor, shopped online for weaponry, and has drafted a suicide note, there is cause for concern.

Morris provides many examples of the added security from student violence that the practice of data mining would provide, but neglects to address in detail the privacy concerns that opening up this information to university authorities introduces. While many of the arguments Morris makes are valid, the article generally seems overly optimistic toward the idea of student data mining. It glosses over concerns of privacy, and of false accusations. Morris uses the example of credit card companies tracking spending behavior to detect fraud. This is a practice I support, as, frequently, it can prevent the owner of the card from having money fraudulently taken away, but credit card companies are not one hundred percent accurate. Sometimes, the owner of the card gets their purchase declined because the credit card company misidentifies suspicious spending habits. In the case of credit card companies, this is fine, as the owner of the card can simply inform the company that there was no fraudulent spending, and the matter is resolved. However, in the case of student terrorist activity, the stakes are much higher. If a student's actions are falsely identified as those of a future murderer, that student can potentially have their life permanently altered by false accusations.

While I have my criticisms of the viewpoints expressed in this article, I do not necessarily completely disagree with it. The issue is a complex one, and I don't believe that there is one correct answer that one can address all of the different concerns and competing priorities when making decisions on whether or not to go forward with mining student data. It's a complicated question that would take much more than 400 words to even begin to try to answer.