Difference between revisions of "Pervasive Surveillance"
Rutland Arms (talk | contribs) (Created page with "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 =...") |
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Pervasive surveillance is the act of capturing small amounts of data from individuals' online activities and storing it to build a profile. | Pervasive surveillance is the act of capturing small amounts of data from individuals' online activities and storing it to build a profile. | ||
+ | The surveillance is often carried out by local and federal governments or governmental organisations, such as organizations like the NSA and the FBI, but it may also be carried out by corporations (either on behalf of governments or at their own initiative). | ||
Revision as of 16:00, 25 March 2019
Pervasive surveillance is the act of capturing small amounts of data from individuals' online activities and storing it to build a profile. The surveillance is often carried out by local and federal governments or governmental organisations, such as organizations like the NSA and the FBI, but it may also be carried out by corporations (either on behalf of governments or at their own initiative).
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.