MCM 0230 S01: Digital Media

it’s easy to ignore free labor in the context of the reading because one labors due to the love of the work and therefore do not necessarily mind the effort required. It’s that easy to change a passion into something concrete all the while producing cultural value. Due to my love of games it would be remiss not to mention mods. Players take the same development kit a developer and choose to create modifications to the existing game that can greatly vary from graphical overhauls, to the inclusion of new items and skins, to even an entire campaign or mode. The more robust mods take a great dale of time and energy to make, yet users make them for their own love of the game, or desire to improve it. There was relatively recent issue with Steam, Valve’s online distribution platform where they were beginning to charge for mods made for Bethesda Softwork’s hugely popular Skyrim. While the argument was made that it would reward modders for their work, but the user consensus that it would effectively warp the landscape of modding and the proliferation of this example of free-labor would stagnate under the pressure of trying to make money off of mods.

Something I found really interesting about Cramer’s “What is ‘Post-Digital’?” is the type of technologies that have become the subjects of nostalgia in the supposed post-digital age. For example, while vinyl has seen a huge resurgence, it would be strange to see a group of 20-somethings picking out VHS tapes at a secondhand store.

I wonder what the difference is between these types of media and what makes a form of “old media” worthy of nostalgia. Is it the time that has passed since the peak of its popularity/usage? Its convenience relative to new media objects? Something else?

Phillips’ “Race and the No Spin Zone” analysis of Internet/meme culture’s inferential racism in the 2008 political election made me think a lot about this recent election cycle. Whereas Phillips argues that the discourse and meme culture surrounding 2008 election was surrounded by inferentially racist undertones, I would argue that the 2016 election cycle, a lot of Internet culture’s focus was centered on a kind of inferential sexism/misogyny.

For example, this article discusses the Bernie v. Hillary meme and the ways in which that meme can be seen as having sexist undertones, although the content/organization of the meme doesn’t seem to be outright misogynistic:

http://www.slate.com/articles/technology/users/2016/02/the_bernie_vs_hillary_meme_is_weird_ceaseless_and_kind_of_sexist_just_like.html

The article explains how the Bernie v. Hillary meme taps into a popular (but not incorrect) idea that Hillary’s campaign tries too hard to relate to pop culture. The article argues that Hillary’s somewhat misogynistic treatment by the media—typifying her as “bitchy” or “manipulative” for a political agency not dissimilar to most male politicians—has left her no position but to try too hard.

Additionally, the article further points out the inferential sexism of the meme. The meme “overwhelmingly situates Bernie’s dominance in masculine subcultures and products,” while it makes Hillary seem incompetent and “try-hard” in these same domains, an extension of an idea that floats around in Internet culture that women feign interest in “nerd culture” (Star Wars, video games, etc., etc.) solely for the sake of impressing men.

Mackenzie Wark’s “Agony” creates an interesting contrast with Keenan’s “Windows.” Both pieces look at the influence the rise of digital media has had on the user outside of the realm of the digital: They look at how the usage of digital media affects people once they unplug and turn off their devices.

Whereas Keenan conceptualizes digital media space as a kind of window that acts as the interface between the private and public sphere, Wark argues that digital media causes a reconceptualization of the outside world into a kind of gamespace carried over from the world of the digital.

The idea of Facebook’s algorithm influencing the ways in which users interact with the content that is shared reminds of me of the debate around Twitter’s recent algorithm change.

Twitter used to have an algorithm that posted tweets of accounts users followed in the order in which they were posted. Recently, however, they updated timeline’s algorithm to one that more closely mirrored Facebook’s news feed feature. Thus, instead of posting tweets in order of the time they were posted, the new algorithm moves tweets of users it thinks you would be most interested in viewing to the top of your feed.

People, in general, were vastly and vocally unsatisfied with this change, proving that even common users are aware of the vast amounts of influence something as simple as a change in the order in which posts are viewed can have on the visibility of a user’s posts and the ways in which other users interact with those posts.

I thought it was interesting how Nigel Thrift’s article essentially historicized modes of thinking. Thought is typically discussed as an immaterial object existing outside the material realm of history; however, by historicizing thought, Thrift argues that it can shaped by external, material forces. Even though thought is often seen as being above and outside history, its exists within it. Not recognizing thought as a product of history, I think, has political implications as well. Anytime something is viewed as without a history, it makes it seem natural– immutable and unchangeable–forever existing in what is actually a historically constructed binary/frame/etc.

I thought the ideas brought up in Keenan’s piece about how windows’ regulation of subjects as public or private is inherently political was especially interesting in relation to modern politics.

Keenan argues that the decision of what to bring in front of the window, and how to bring it in front, and therefore into the public sphere is an inherently political one. I thought that was especially resonant in light of the Huffington Post’s representation of Donald Trump during the 2016 election cycle. Originally Huff Post put Donald Trump under the entertainment section of the paper. Later Trump was moved to politics but every article was tacked with an editor’s note identifying Trump as a racist, xenophobe, etc. This is an example of how the ways in which someone is brought into the public sphere can be influenced by how they are brought in front of the window and framed. Reading an article about Donald Trump in the entertainment section of a paper has a different effect on a reader than reading about him seriously in the politics section of the paper alongside candidates like Hillary Clinton and Bernie Sanders.

The notion that big data moves from technology from description to prescription was particularly salient to me coming out of lecture on Tuesday. Computers are no longer describing our world, but actively shaping what it becomes. This idea is particularly impactful when compared to our discussions of race and sexuality. Since computers internalize current biases, any predictive capability will reflect our prejudices. ‘Prescription’ also has a normative connotation; we see computer predictions as generating what ought to happen in the future, not just what is likely. This difference is very significant, because it implies that we value the output of big data calculations. Even if an event is unlikely, if a compute predicts it, we are likely to follow the technological predictions because we see them as morally good. For example, we do not know if the global warming prediction models are true, but we value computer output, so we are likely to behave as if they are. I wonder whether this conflations between should occur and ought occur has serious consequences our society, especially given that we systematically overlook the fact that computers are performing biased calculations.

There’s an interesting intersection of big data and personal data in the field of personal informatics. Each year, more people invest in wearable technology – FitBits, smart watches, and other digital trackers. The data monitored by these various devices is deeply personal. The majority of an individual’s life can be encoded in this data.

In and of itself, this data can be considered big data. With so many sensors collecting so much data, each device has its own stash of big data. However, this data is also personal – more personal than shopping habits or other online activities. Included in this data are heart rates, blood sugar, and other vitals. It’s not the sort of data that should necessarily be in the hands of impersonal corporations.

I mean to call into question the continually growing collection of personal data by consumer corporations. This collection uses the customers of the company, who believe that they are making a one-off purchase of a product, as laborers who collect data every waking moment of their life.

Towards the end of this course, we have focused on big data and free labor, two aspects of the modern digital which seem highly interconnected to me. One of the questions in Monday’s lecture was: “Can you have big data without free labor?”

Every click is stored across time and space as big data. This information, our clicks, are stored and used for things like Netflix recommendations and personalized ads.  Our clicks and the big data that they contribute to are doing work for Netflix and google ad algorithms. Each click is being stored for a reason, to do some sort of work.  Big data exists because of political decisions for it to exist. The data is being stored to collect more information about us as people, instead of things like focus groups or in-field researchers collecting this information.