Predictive analytics might not have predicted the Aurora shooter by Robert L. Mitchell.
From the post:
Could aggressive data mining by law enforcement prevent heinous crimes, such as the recent mass murder in Aurora, CO., by catching killers before they can act?
The Aurora shooter certainly left a long trail of transactions. In the two months leading up to the crime he bought more than 6,000 rounds of ammunition, several guns, head-to-toe ballistic protective gear and accelerants and other chemicals used to build homemade explosives. These purchases were made from both online ecommerce sites and brick and mortar stores, and more than 50 packages were sent to his apartment, according to news reports.
Robert injects a note of sanity into recent discussions about data mining and the Aurora shooting by quoting Dean Abbott of Abbott Analytics as saying:
Much as we’d like to think we can solve the problem with technology, it turns out that there is no magic bullet. “Something like this could be valuable,” Abbott says. “I just don’t think it’s obvious that it would be fruitful.”
That would make a good movie script but not much else. (Oh, wait, there is such a movie, Minority Report.)
Predictive analytics are useful in the aggregate, but we already knew that from the Foundation Triology (or you could ask your local sociologist).