Pervasive Surveillance

Pervasive surveillance is the act of capturing small amounts of data from individuals' online activities and storing it to build a profile.

Case Study: Disease tracking

In 2009 Google published a research paper documenting a method of tracking influenza-like illness's spread in a population by analyzing large numbers of search queries. It was reported that Google could accurately measure the influenza activity in each region of the U.S.A. with a record breaking report lag of one day approximately. The usual reporting lag via the usual method of waiting for clinics to report cases was two weeks.

Case Study: Target

Andrew pole, chief data scientist for retail chain target, successfully implemented an algorithm for detecting whether a customer was pregnant via analyzing data the company collected on their spending habits he was able to identify approximately 25 products that when bought in combination could be used to assign a score to each customer predicting their likelihood of being pregnant. The algorithm could even track individual stages of pregnancy, coupons could then be send enticing customers to buy. At once point the algorithm even predicted that girl was pregnant before even her father knew.