Online Surveillance and Computer Science no comments
It is understandable that governments are becoming increasingly interested in the online activity of its citizens. According to Albrechtslund, governments are looking for information about individuals such as “shared activities and circles of friends, as well as personal data about political views, religious beliefs, sexual orientation, and preferences regarding everyday life activities (Albrechtslund, 2008). Social networking sites are for example used to get this information. The information that governments often want can also be stored in email conversations, on personal computers, in the cloud and so on.
Computer science can offer many perspectives on online surveillance. It does not necessarily look at the motives for or consequences of surveillance, like psychology does, but can focus on how surveillance is made possible or can be prevented through a technological perspective. It can address all the different phases in the process of online surveillance from the ‘Big Brother perspective and from the perspective of the person who is being watched. This means that it can look at where to look for useful data, how to retrieve this information, and how to analyze it, but at the same time it can look at how to prevent people spying on ones data.
Examples of where computer scientists thus might look for could be where data is stored on personal computers, how this data can be accessed, how encryptions can be created or cracked, which algorithms represent useful data, and how retrieved datasets can be analyzed. In many possible examples creating programs that can scan large and varying sets of data are important. Also, it is necessary to let these programs find specific words, websites, connections and so on, that might be interesting for the party that is watching.
Next time I will write my last blogpost about how computer science and psychology are related and how they can be bundled to study online surveillance.
Source
Albrechtslund, Anders. (2008) ‘Online Social Networking as Participatory Surveillance’, in First Monday, 13(3), online at: <http://journals.uic.edu/ojs/index.php/fm/article/view/2142/1949>