Eagle Eyes

The biggest question that had arisen in my mind while reading for this week is “Can you choose to opt out from such data collecting and surveillance?”. There seem to be three elements that would make it difficult for an individual to escape from the data collecting activities — invisibility, inconvenience, and infrastructure.

Invisibility

One of the reasons why an individual wouldn’t be able to withdraw from having your data being collected is because it is not readily visible to her. In Rita Raley’s piece, “Raw Data” Is an Oxymoron, she discussed how Adobe System’s privacy setting is hard to navigate that it appears “as a demo rather than an actual window”(Raley 122). Although the setting dashboard is physically ‘visible’ to the user, the user is not aware of its function and thus loose the ability to set the preference to her/his liking.

Inconvenience

Similarly, inconvenience comes into play when such setting for a system is ‘invisible.’ As I have mentioned in the previous piece about FitBit, the company had the default privacy setting to be public. Even though the users had to agree to the term of service, which had written statements about the default privacy setting, it is extremely inconvenient for people to read all the agreements, especially when people can be signing up for multiple services in a day. Also, while the FitBit users had an option of manually changing the privacy setting to be private, the required extra step made it less likely for the users to change the settings.

Embedded Infrastructure

Even when we step away from the data that are being collected through our devices, whether it is personal computer, browser, mobile device, etc., now we are living in the world where you can be ‘seen’ from anywhere. Let’s retrace my morning commute from home to school to see how much of my personal data is being and can be collected en route.

First, when I wake up in the morning, I hop into the shower and prepare a simple meal for myself. My activity using gas and electricity is logged into the database of my utility provider, showing how much energy I am consuming each day, and when I am actively engaged with the system (data 1). After I get ready to leave the house, I step into the elevator to get down to the street level. The security camera in the elevator streams or stores a video of me, knowing when I’m leaving my house (2). Then I would go to the bus stop and wait for the bus. Once the bus arrives, I tap my student ID card on the bus fare reader. It indicates that I’m a student from Carnegie Mellon University (I assume that each card is assigned a specific code that allows each student to get a ride). It knows where I have gotten on the bus (3). Also, the security cameras on the bus are recording my activity on the bus (4). After I get off the bus, I head to the coffee shop at Gates and Hillman centers. Before I can enter the building, I have to swipe my ID card to gain access, and the system knows that I have entered the building(5). I get in line to get a coffee and pay for it with my credit card. The price and the name of purchase — Latte — get recorded at the credit card provider system(6). Also, again, all the activities that are being held in the building until I exit the building get recorded by the security cameras installed throughout the building(7). With a cup of Latte in my hand, I walk across the campus and arrive at Margaret Morrison building. I walk up the stairs to the second floor. When I swipe my card at the entrance to enter the space, it logs that I have come into the studio(8).

As I have listed out above, my commute — even when disregarding mobile phone activities, such as GPS on Google map, mobile banking, reading news articles, listening to music, browsing websites, etc. — involves at least eight surveillance/data collecting system.

When living in the modern society, it is impossible for an individual to simply ‘opt out’ of being watched. However, what needs to be addressed is how each individual can be aware of the data being collected and gain control over it through a clear representation and transparency of the system.

• Alice Marwick, “How Your Data Are Being Deeply Mined, New York Review of Books, January 9, 2014 [Box]
• Rita Raley, “Dataveillance and Countervailance,” “Raw Data” is an Oxymoron (Cambridge, MA: MIT Press, 2013), 121–45. [Box]
• David Cole, “We Kill People Based on Metadata,” New York Review of Books, May 10, 2014. [Online]