I thought that Lev Manovich did a good job in his article explaining why he thinks that the emerging form of big-database could benefit not only the sciences, but also humanities. I absolutely agree that with the development of new technologies and databases, the capacity for scientific research and the study of humans will only improve. However, I did appreciate how Lev Manovich also stated way in which the changes in the way people collect data and manage data could also affect research and people in a negative way. Manovich listed four arguments against his claim that big-databases could affect the sciences t which I agree. I think that the emerging forms of database are a good thing for research, but I do see how they could have questionable influences on the media. The first argument being the amount of data people would have access to With the amount of information that is now able to be stored and accessed by certain companies or individuals, I think that it is a liability having a large amount of information being accessible to one entity or person. For instance, the controversy over the newly developed program by google, where google could access your accout information and use that information for advertising purposes. Large amounts of data do need to be managed properly in order to prevent controversy. The second argument was that not all the information collected online is accurate, which is absolutely true. On social networks people post and comment according to what they want other people to think about them. People can filter what they share or lie about what they share to others. Also certain websites have different political views or outlooks on fact and can interpret information differently. The third argument addressed how information could change through the proxy by which it is obtained. An Anthropologist will gather different information if it is gathered by human interaction rather than through technology or computer data. The information being obtained is subjective based on how it is collected. The fourth argument is that in order to be able to fully use the technology to its full advantage, one must be able to understand the computer language. People will not eb able to benefit from the new form of data if they are not familiar with the proper education.
Poetry and poker
Poker was never my cup of tea. It was one of those things I wanted to be good at just to look cool, but it failed as I still remain a horrid poker player. I was given a second wind, however, when I spent about an hour with Stud Poetry by Marco Niemi. In the game only your words have values because the goal is to construct the strongest poetry–and win money, too!!–line you can muster with the cards you are dealt.
The objective of Stud Poetry is to create the best poetry line possible, using words that are “dealt” to you. The player is only given the option to “call” “raise” or “fold,” and, from this, the player determines the value of the words dealt–just as in poker and how the many combinations of suits have a particular value–which is interesting because all writers use specific words for their particular writing style and most writers have a unique style and vocabulary. When you have a bad hand, however, the only logical option is to fold, but at times, I felt as though my words were decent–I could have smashed together something creative, poignant and deep with the words I was dealt; however, compared to the other AI-controlled players, their word combinations surpassed my own.
After my short time with Stud Poetry–I still, unfortunately, suck at poker, and I’m a pretty bad poet, as well–what I took from this work is a better understanding of how difficult it is to create great poetry. Before taking this class, my view of poetry continued to flip-flop; either it was a bunch of words slammed together, luckily creating a work that filled the souls of readers with intellectual satisfaction, or the words are personally and specifically chosen by the poet, so that his or her emotions aren’t misinterpreted. Poetry and poker is an awkward mix, but then again, what isn’t awkward in new media?
Social media as data
Lev Manovich’s article “Trending: The Promises and Challenges of Big Social Data” discusses the emergence of vast amounts of data that may soon be available to researchers in the humanities field. In particular, he addresses the problems and complications which could arise with this data, one of which was particularly interesting to me.
Although social media sites will soon prove to be a great resource in terms of data for the humanities, Manovich urges that we must be careful when interpreting this data. While it does allow for a much larger sample population than many past studies, social media information is largely biased and in many cases does not represent the actual thoughts and emotions of the people posting it. While some users may be posting their real thoughts and feelings, others may post only things that their friends want to see, or will refrain from posting things that they think do not fit the social norm or which they might be judged for. I know that I myself would be an example of this case; there are many times when I do not post things on social media sites that I feel like my friends would not want to hear about.
This point of his article made me realize just how different the data used in the humanities is from the data used by sciences. The large amount of data that can be obtained from social media sites can almost all be biased in one way or another, whether a person is simply posting a status that is different from how they really feel, or taking pictures that only portray a more positive image of themselves. The data used in science, on the other hand, can be thoroughly researched and proven to be true. Although this may have been an obvious difference to some, I had never before considered the possibility of researching vast amounts of social data in the humanities field that is taken from people’s personal profiles, rather than from facts collected by the government. When data from social media is analyzed, it seems to me that it should be read more as trends of what other people want to make their peers think about them. While it could be used to analyze social trends, I believe these vast amounts of emerging social data should also be analyzed carefully, and taken with a grain of salt.
String Theory
Strings is a piece of electronic literature based on human relationships and is presented through handwriting. The Flash program goes through various human emotions, actions, or dialogues that occur within a relationship, such as arguments, flirtation, and laughing, which take form as animated and morphing lines of cursive writing.
Two arguments are presented that vary from a linear yo-yoing back-and-forth between “yes” and “no,” and a floating “yes” and “no” that is accompanied with a lingering “maybe.” One form of flirtation is presented as a slowly scrolling “no” that morphs into a “maybe” (there is no “yes”), while the other is dominated by “yes” that flirts with the screen by “dancing,” twisting, and turning about. In arms, a squiggly line forms into four items: “your,” “arms,” “O,” and “me.” Audiences are left to interpret the meaning of “O,” however it is somewhat apparent that it means “hold” or “embrace” given that the “O” rotates (when the other words do not). The last animation the program leaves you with is entitled poidog. In it, a single squiggly line rapidly morphs to form the words/sentence “words are like strings that I pull out of my mouth.” This final thought connects with how this piece is presented: all the emotions seen are represented as strings of thought and manifested as strings of writing. The choice of cursive font over standard type is appropriate because, requiring unbroken and continuous flow, it mimics both the appearance and movements of string.
The fact that this piece of electronic literature is presented in handwriting at all and not an obvious computer font lends to the personalization of the experience. Contrary to “killing off the author,” Strings is dependent on its author to convey the presence of “the hand” and the human in an interface/medium that is notoriously devoid of it (meaning completely computer-focused). This piece is a great example of what Lev Manovich referred to as surface and deep data in “Trending: The Promises and the Challenges of Big Social Data.” Strings was generated as a type of “deep data” to convey the emotions about a select few individuals (namely its own author). But, in being posted and shared with the internet, it has transformed into a sample of “surface data” that is representative of how similarly its audience may feel. As Manovich puts it, “one pixel comes to represent one thousand” (462).
Inanimate Alice: Storytelling of the Future
Inanimate Alice, written by Kate Pullinger is an “educational digital game.” However, while going through the first eight minute episode, it didn’t feel like a game. Other than one interaction where the “player” has to click on flowers in the field to take a picture (which didn’t really seem to work that well, but my computer could be at fault), the player doesn’t really play the game. As far as I could see, the only other interaction was the clicking of arrows to go further in the story. Nonetheless, this works as effective interaction.
While Inanimate Alice lacks the interactive structure that I’m used to finding in a game, it does work successfully to show how our lives are intertwined with technology.
Alice and her parents live in a rural environment where I would imagine that technology would not play that great of a part. Instead, Alice finds refuge in her imaginary digital friend Brad that she can view on her phone device. When her father doesn’t come back from his job, Alice and her mother take their jeep and go looking for him. A good part of the narrative is Alice exploring her device by taking pictures, looking at Brad, and stating what she’d rather be doing than searching the desolate and frightening landscape for her father. Alice uses technology the same way I do: when I’m bored and in a sense, when I want to escape reality.
While commenting on our near-future, if not already present digital age, Kate Pullinger and Chris Joseph use a mix of images, music, text, and easy puzzles to create Alice’s story. I believe that Inanimate Alice could be very effective way of storytelling for future children born in the technology era by communicating with them through the medium which they are most used to.
Tactical Media as a form of Political Dysfunction
Rita Raley’s description of tactical media simulates Marie-Laure Ryan’s concept of dysfunctionality in “Between Play and Politics: Dysfunctionality in Digital Art.” Raley offers several definitions or conceptions regarding tactical media. First and foremost, “tactical media signifies the intervention and disruption of a dominant semiotic regime, the temporary creation of a situation in which signs, messages, and narratives are set into play and critical thinking becomes possible” (Raley 6). Works of tactical media are created to disturb, question, and momentarily corrupt an alternate form of media that demonstrates principles with which tactical media creators vehemently disagree; such creations are used as a means of critique and provocation of thought regarding a social change that tactical media attempts to re-examine. Tactical media is meant to “present a challenge to ‘the existing semiotic regime by replicating and redeploying it,’” forcing viewers to react to and engage in such social change (Raley 7). Raley’s explanation that tactical media disrupts other media forms complies with Ryan’s theory that dysfunctionality seeks to interrupt technology by using such technology for disparate purposes other than that which the equipment was created.
Ryan provides an example of a politically dysfunctional technology called the Image Fugurator, which distorts other camera’s pictures by implementing political text into the photos. The Critical Arts Ensemble (CAE) states that their goal in such dysfunctional acts is to “exercise electronic resistance to the governmental and corporate forms of power that rule capitalist society by attacking the database maintained by these institutions” (Ryan 2- put hyperlink). Similarly, the CAE determines the purpose of tactical media as “’offering participants a new way of seeing, understanding and interacting’ with ‘[the invention of] new spheres of reference…to open the way to a reappropriation and a resymbolization of the use of communication and information tools…’” (Raley 8). Tactical media can be viewed as a form of politically dysfunctional technology that aims to disrupt social institutions by which society is constrained and to offer alternate views of thinking about such societal norms.
Raley demonstrates that society has been interpolated—the recognition of being restricted by societal norms—by various societal ideological state apparatuses (ISA) that confine and constrain society. Tactical media thus serves to question and even break such interpolation by making ISAs powerless. For instance, Ubermorgen designed a piece of tactical media that allowed users of Amazon to be able to pirate and disseminate copyrighted books (Raley 19). Amazon, a representation of a governmental ISA that defines the societal norm of capitalism and consumerism, was temporarily incapable of affecting or influencing society as this form of tactical media disrupted the purpose for which Amazon was created. Tactical media is not a form of arbitrary dysfunction, but serves to utilize such dysfunction as a tool to spread a political message and critique. While it is evident that tactical media succeeds in broadcasting a political message that forces viewers to re-examine social norms, the method by which they proliferate such information imposes and infringes upon the abilities and functionality of foundational organizations. Furthermore, does the end product of such infringement counteract the violation of others’ rights or do the means to achieving political activism corrupt the purpose and message?
DEATH SPIN
This is How You Will Die by Jason Nelson. Once again I partook in a Jason Nelson experience, and it was absurd, and refreshingly disorienting. The way it works in one sentence is you press a button on the right labeled “Death Spin” which throws the digital slot machine into motion, which shortly weaves together a 5 part narrative of your death including post death happenings, as well as specific and absurd death realities and you can only find the right one if you satisfy the game’s criteria that is, you must have fewer than 10 death credits to stop. I stopped with 2 death credits and therefore could not continue to “forecast my death.” I was left with an interesting post death detail: “And sperm you donated in college accidentally impregnates a tornado victim.” Even though the author is now dead, (brutally murdered by Engl376/508 a few classes ago), I can’t help but wonder about Jason Nelson’s intentions for this piece of new media art. He seems to have an attraction to the absurd in his work, and I think that dark humor is also a component as well; I feel like he wants me to bask in the rays of confusion that the death machine generates. However, thinking of Nelson as the author allows me to make more sense of the piece; it lets me place the work in a grounded time. Therefore, maybe I should not be thinking of him at all, and truly embrace the full reduction to absurdity by participating in the slot death free of authorship; as a separate entity of the internet world capable of transporting me to a place where I can ponder paradox and existential questions. I thought about making a narrative map of the many possible death sequences, but then also questioned its effectiveness: is slot death meant to be unraveled? I don’t understand the death videos, but, they are a nice bonus to getting me to that special place.
Can Disruptive Data Exist?
Manovitch (“The Database”) and Raley and the yearn for a disruptive artwork. Both scholars push for a Data-based artwork that does more than represent. Raley specifically mentions the way that Tactical Media can “disrupt” normal society.In the introduction of Tactical Media, she mentions hactivists shutting down or changing websites temporarily as an example of this – this example I understand. But some of her examples in the chapter of Speculative Capital do not seem disruptive to me. Black Shoals and ecosytem are provocative, fit into Manovitch’s specifications of a database, and successfully create a narrative of data through their visualizations – Black Shoals with the story of an economic universe and ecosystem with the progression of the birds movements and actions. Raley specifically mentions that these artworks are disruptive.
I don’t know about you; but when I imagine disrupting the stock market, I imagine a scene from the most recent Batman movie. Perhaps I am thinking of the word “disruptive” in too concrete terms but even when I try to conjure up ideas of how the artworks disrupt in abstract senses, I am unimpressed with my result.
- The artwork disrupts the viewer’s day. This greatly belittles the salient and serious subjects of the work.
- The artwork disrupts the stock market. Nope.
- The artwork disrupts our understanding of economics. Maybe?
I could see option 3 working out but I would argue that “disrupt” is not the right term here. Educate, perhaps is. In fact Raley actually speaks briefly about education, but doesn’t give it enough credit. And maybe educate is not the right word either, if you already have a good understanding of the way the economic world works. In that case, confronts is best. These works confront us with a new visualization that might make us think critically about capitalism and monetary standards. By making it immediately visual, it brings the ideas to the front of our minds – and I am nor sure if that is disruptive or not.
Big Social Data
In one of my favorite articles we’ve seen so far this semester, “Trending: The Promises and the Challenges of Big Social Data,” Lev Manovich proposes a new type of humanities student and scholar: the kind that can both think and analyze like an English major, but also research and construct digital environments in which to host and process their work like a computer scientist. During this whole class, I have wondered about digital media as a study of English and literature, especially when considering what kind of (albeit “stupid, little”) digital object I, and the rest of the class, would create. I’ll assume we all have the capability to dream up digital objects that crunch numbers, move wildly about the screen, or aggregate all instances of certain themes on the world wide web, but…are we capable of actually creating those objects? Manovich says that, “if each data-intensive project done in humanities would have to be supported by a research grant which would allow such collaboration, our progress will be very slow,” indicating that we (as humanities students) may not currently possess the ability to program or write code and algorithms necessary to do the type of “big data” research we would like to, and we’d better start enrolling in IT and computer literacy classes in additional to contemporary lit and cultural studies classes.
I definitely think Manovich is right, that the humanities (and particularly the college major course requirements for humanities) could use an infusion of computer science. That said, I think most courses of study could benefit from this infusion. Not only can computers help us to parse big data useful for humanities research, they and (knowledge of/about them) can help tackle all sorts of hurdles more easily accomplished by an algorithm than “by hand.” I work as an online sales manager for a small business, and I totally understand what Manovich means when saying that you sometimes need to have specific computer knowledge in order to collect the types of data you want. If I want to organize inventory in a specific way or track trends in sales that are not “pre-supported” in the algorithms that the program automatically offers, I have to create myself a new Data Import file or a new Data Export file, that tells the program how I want it to read the information that I will upload into it as en excel or text file. This is not something I was trained to do or previously had knowledge of, and as a result has caused me to seek out a lot of computer skills knowledge that I didn’t already have. Gaining this knowledge and ability to manipulate inventory and sales data through the computer has not just benefit my understanding of the company’s fiscal position, but has allowed me to more thoroughly analyze trends and make adjustments to the way we do business as a result.
Maybe this is because I don’t know too much about how programming works, but the one question I did keeping asking myself throughout reading the article (especially when Manovich is talking about reducing the “data landscape” to a useable size) was: What are the computer algorthims for videos, photos, and non-text datas based on? How would you ask the computer to put constraints on the data set? Are these constraints based mainly on the “formal” aspects of the data, i.e. time, date, length, size, color, original tags or descriptions associated? How would you organize the data by themes, if all you had was length of video and file size? For that matter, how would one organize the data based on any content with physically watching all 1 million videos and tagging them all with relevant terms? For that matter, wouldn’t doing something like that result in a fairly subjective idea of what the themes or content of each video is?
“Flight Patterns”
“…mapping art still is the result of an artistic process, including the choices of which data are to be mapped and the decision of how to visualize them” (Simanowski 175)
In Flight Patterns, UCLA artist Aaron Koblin has taken data provided by the FAA and mapped it into an electronic visualization using Adobe After Effects and/or Maya, motion graphics and animation software programs respectively. These flight patterns are represented in lines of color, superimposed over a black background. Depending on the user’s preference, the data can be viewed by altitudes, model, or manufacturer. The lines begin and end in cities around all over America, and in each view the outline of the United States can be made out, as well as educated guesses about where each of the major cities are located depending on the concentration of light in certain areas.
More interesting than the static screen shots is the YouTube video depicting flight patterns, and the number of airplanes from 5 pm eastern time to 8 pm eastern time the following day (27 hours worth of data). During this 57 second video, the multi-colored flight lines move according to the schedules of domestic and international travel. Around 1:30 am EST, the map is quiet and dark, with only 4000+ airplanes in the air. Soon, between 2 am and 5 am EST flights begin to take-off from the west coast towards the east (appropriately symbolically red, since many of these flights are named “red-eye” flights). As these flights stream over to the east and land around 6 am EST, suddenly the east coast lights up as thousands of flights take-off west, south, and north. Around midday the transatlantic flights are beginning their arrivals onto the eastern seaboard. A spray of blue flight lines pour from the right of the screen where Europe is obviously located.
The 57 seconds of activity is not only visually mesmerizing, but elucidating as well. This is simple data content in a breath-taking form. With the satellite-eye’s view of the transactions taking place in just over 24 hours (likely repeating itself every 24 hours), the sheer magnitude of planes in the air – 19200+ at its peak at 4 pm EST – gives the viewer an appreciation off all the activity managed by the FAA, for example, as well as a take on how many human bodies are thousands of feet in the air at any given moment! When the viewer takes into consideration the individual life-narratives of each passenger and multiplies that by X passengers in X planes on X flights…the data is overwhelming. What an effective interface to make that kind of information accessible and appreciable.