#boxerpride

By:

Calli Hayes 

Cassie Apple 

Kendra Bailey 

Mariam Rija

1. What are algorithms and what do they do?                                       

From a mathematical, computational view, Gillespie explains algorithms as “a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer. Algorithms exist that perform calculation, data processing, and automated reasoning” (Gillespie, n.d.).  He continues by explaining “algorithms need not be software: in the broadest sense, they are encoded procedures for transforming input data into a desired output, based on specified calculations” (Gillespie, n.d.).  Algorithms serve an important function from a sociological perspective as well because they structure how we receive information and “sequence the social world,” (Beer, 2013).

2. How do they shape our encounters with information?

Algorithms shape our encounters with information by narrowing down the numerous amount of data from a larger database (Beer, 2013). Algorithms select information that is most relevant to the individual’s search request. An example of this would be Netflix, and their use of a recommendation algorithm. Netflix uses these algorithms to help consumers find the movies and shows they wish to watch. By keeping record of what an individual has watched, the algorithms create a list of recommended movies based on the type of shows you have watched in the past. Using such algorithms make finding what one is looking for much easier and is convenient for consumers. Here is an example of how netflix uses algorithms to suggest new movie titles to one’s personal interests.

3. How are they related to the “technological unconscious?”

"Technological unconscious” refers to “the relative invisibility of the infrastructures and infrastructural processes around us,” (Beer, 2013). In other words, algorithms are one of many examples of “the operation of powerful and unknowable information technologies that come to ‘produce’ everyday life (Thrift, 2005).  Without much human intervention or awareness, we accept algorithms as part of everyday life and rely on them to perform functions for us. By simply entering things we like to watch, algorithms Netflix uses produce suggestions without us inputting any other information or doing any work. 

4. How are they related to human agency?

Algorithms are related to human agency as they use our data input into the social world, such as social media, and using it to pinpoint our interests and feed us information to indulge on the things we take interest to. Beer (2013) explains that “software algorithms...are deeply embedded in a range of social spheres” and while it may seem like human input or discretion is no longer taken into consideration, this is not the case. Since algorithms do not exist independent from the human world, “the design of the algorithm then is very much a product of the understanding of the outcomes it is likely to create and is therefore shaped by the judgement of the designer,” (Beer, 2013). Returning to the Netflix case study, we see that it is indeed a two-way street with Netflix’s predictive algorithms functioning by analyzing human behavior and responding to our responses to its suggestions (Beer, 2013).

5. How does information make algorithms lively?

As stated above, algorithms shape our encounters with information by using codes to make a picture or image to help us understand the information presented to us.  The constant influx of information that is instantaneously compiled affects what algorithms reflect, which in turn influences future actions, making algorithms lively (Thrift, 2005).

6. How are algorithms related to social norms and capitalist ideology?

“The ‘new spirit of capitalism’ (Boltanski & Chiapello 2007) gets inscribed in the fabric of search algorithms by way of social practices...both website providers and users stabilize the algorithmic ideology by entering alliances with search engines to reach their own goals ” (Mager, 2011).

7. How might algorithms complicate old theories about how we encounter culture and/or how tastes/preferences are shaped?

The digital age has transformed and altered many facets of life, including cultural formation and the formation of individual identities and selfhood.  Prior to the usage of algorithms as seen in today’s digital age, thoughts and questions were internal and private, and a print dictionary, encyclopedia, or trusted friend or scholar served as the mode for receiving answers.  Answers came from unresponsive inanimate objects or a select group of people.  With algorithms, we see google providing commonly searched phrases using data agglomerated from every user globally.  In the case of Netflix, movies and TV series were recommended by friends and perhaps the Blockbuster employee as you browsed section by section for something appealing. Now, the abstract movie you watched and rated signals Netflix to suggest an oddly specific film recommendation that sometimes perfectly suits you, whether you were looking for such a film or not.  Previously unknown genres, shows, and movies that you could only encounter if it caught your eye by chance while perusing the library’s VHS collection are now at the forefront of your own personalized queue.  A Netflix algorithm produces a sense of autonomy and individuality as you are able to occupy a specific niche and consume products of the entertainment industry at your leisure and specifically suggested to you (Thrift, 2005).  This extends and produces simultaneously a culture of individuality while also an interconnected society reliant upon one another.  There is no obligation to watch the same show as everyone else because there are no longer limitations such as time dictating when, where, and what you can watch.  However, data Netflix collects demonstrates which shows are most popular among people and presents these shows more frequently and on the front screen.  Netflix users are now aware of what others in society are fond of and can also watch the same shows, which facilitates social connections and opportunities for conversation and discussion.  Also, without the information of other Netflix users, the algorithm cannot exist and there would not be a way to infer what the user might like based on previous selections.  It is only by observing what others do that Netflix can understand someone’s tastes and preferences and also develop them as a result of providing suggestions.  

  Bibliography

Beer, David. 2013. Popular Culture and New Media: the Politics of Circulation. Palgrave Macmillan UK. 

Gane, Nicholas and David Beer. 2008. New Media. Oxford: Berg. 

Gillespie, Tarleton. n.d. “The Relevance Of Algorithms.” MIT Press. Retrieved January 27, 2016 (http://mixedrealitycity.org/readings/gillespie_therelevanceofalgorithms.pdf).

Kennedy, H., T. Poell, and J. Van Dijck. 2015. “Data And Agency.” Big Data & Society 2(2). 

Mager, Astrid. 2011. “Algorithmic Ideology: How Capitalist Society Shapes Search Engines.” SSRN Electronic Journal SSRN Journal. 

Mei, Christian. 2014. “Algorithm And Data Structures - Basic of IT Problem Solving.” Linkedin. Retrieved January 27, 2016 (http://www.slideshare.net/coolpie/algorithm-and-data-structures-basic-of-it-problem-solving?qid=f1be517b-f3d4-4273-9946-e0ce765258ae). 

Tanguturu, Saikrishna. 2014. “Computer Graphics - Bresenham's Line Drawing Algorithm &Amp; Mid Point Circle Algorithm” Linkedin. Retrieved January 27, 2016 (http://www.slideshare.net/saikrishnatanguturu/computer-graphics-ver10?qid=4ad8fd25-d035-49c7-86d3-a1592c6f91cf).

Thrift, Nigel. 2004. “Remembering The Technological Unconscious by Foregrounding Knowledges of Position.” Environment and Planning D: Society and Space 22(1):175–90.