Grace Logan, October 23, 2020
Post-productionTo summarize some of the interesting points made in class yesterday, we have come to an understanding that data is a representation, which implies interpretation. To go further, data is a social fact and is socially produced, I think this is related to the statement Professor Himpele made about data being instrinsically partial and incomplete because choices about the data are being made by some data collector/presenter. I used “collector/presenter” intentionally to relate this to the digital data and culture visualization that Rei, Matthew, and I made in Miro. In our visualization we attempted to demonstrate the implied interpretation of data, a representation, by showing what cultural factors may influence the interpretive process. One thing that I would like to change about our visualiztion after yesterday’s conversation is the location of the digital data. Though we discussed as a group how culture can be the context that the data is understood in, and we attempted to show how their are multiple points of view involved in the whole process of collecting, presenting, and consuming data, I think that locating digital data is some sort of cultural web would be a more helpful representation.
Towards the end of our discussion yesterday what really intrigued me was the idea of data protection and regulation. My question in Miro was about why is it that only some research is restricted by institutions like IRB. As Boyd and Crawford mentioned there is contention over how ethical it is to use “public” data that may not be intended to be viewed by all of the public (p. 673). I am not that familiar with data protection and regulation, but it seems to me that mostly educational/academic, health, and financial data are regulated. I wonder if this reflects how valuable this data is or how at-risk it is of being used inappropriately. Maybe the gaps in regulation are just reflective of the ongoing argument on how to regulate some newer forms of data like internet social media.
Ailee Mendoza, October 23, 2020
Post-productionI was really intrigued by the MP3 piece this week, especially with respect to the concept of selling an experience. I am honestly still struggling to wrap my head around this (I just think it’s really cool), but the line that stuck out to me from Sterne’s piece was: “If sound is not ‘out there’ but rather created by the process of perception, then the mp3 is not a simulation of sound or a virtual sound. It is simply another mode through which the effect of sound is produced and embodiment is the defining characteristic of the experience.” He then goes on to say, “The point of recording and reproduction is not to mirror sound but to shape it actively.”
I really liked when Zack said in class that Big Data is not a concrete, fixed “thing,” but an interactive or dialogical process. It makes me think about all these 0’s and 1’s differently, or I guess data in general; in order for the data to serve its purpose or to represent what it’s encoded to represent, we– as humans with mechanisms of interpretation (i.e. auditory perception)– have to meet the data halfway. The mp3 is not a standalone “thing” either. It encodes the effect of sound, as Sterne says, but makes us do the work to interpret it as music. Could the same thing be said for data? I guess, right? This brings me back to the privileging of context. On the most rudimentary level, a set of data points has meaning unless a key, a scale, or a set of corresponding values is given. These contextual cues and the interpretation they amount to are like Sterne’s “effect of sound.” In fact, they’re more than that– they’re greater than just the sum of their parts: they create a physical, embodied experience. It requires our brains, as active interpreting machines, to interact with these concrete entities that would otherwise have no real significance. I feel like I just rewrote my midterm essay, but I’m interested in how much “mythology” as Boyd and Crawford referenced in their piece, is a factor in these things we label as objective, digital, and non-human. Since when did data and technology become associated with objectivity?
Lauren McGrath, October 23, 2020
Post-productionI wanted to expand upon our discussion of what constitutes a “person” in the context of my independent work, from previous literature in the class, and in reference to my group project for this class on the pandemic.
I first stumbled across this notion of defining what a person is and is not in my independent work; I’ve observed a sharp division in the neighborhood and area that I’m collaborating with in Philadelphia between those who are residents and others that occupy the same geographic space but are not considered residents. When pointing out the non-residents or “others,” oftentimes comments are made about their behavior and decisions, which drives me to question if personhood could be at least partially based on what is culturally normalized about how a person acts and behaves in public. I also wonder if the ability to collect data on an individual defines personhood, as we briefly discussed in class. Many of these others/non-residents/drug-addicts do not have a permanent address or a credit card number. Does lacking this data mean they are less of a person? Another example of personhood manifesting in data collection is data I found on naloxone administration, in which the data’s label was “naloxone administered;” this passive language leaves out the context of the human-to-human relationship and interaction that occurred. If the government expanded this label, would they include naloxone administered to a person/human/drug addict? I’m wondering if they would label it as “the unconscious” which is another layer of personhood; is a person defined by their consciousness? As you can probably tell, I have more questions than answers for this topic.
I think there is a connection here to the Rodney King video, where the defense added their own context to depict him as animalistic, and therefore less of a person. To me, this case reinforces the cultural norm that society believes that an individual on drugs, or possibly could be on drugs, occupies a state that doesn’t categorize them as human or a person. Is the data collected on drug users, labeled with this passive language, reinforcing these cultural norms of personhood? I’m really interested in the societal structures that set these standards of determining personhood; I think they are complex and entangled but are reinforced by current cultural norms.
Switching contexts, I think the language and the graphs/charts used in the media and local news channels describing the COVID19 pandemic could be an interesting site of further discussion for us all: I feel like I hear the words “cases” and “deaths” without the direct link to the human/person. When we use terms such as cases and deaths rather than “human deaths”, are we implying that there is a shift in personhood or agency from a person who is COVID-free to an individual as a “case”? I’m wondering why we are taking this impersonal view on the pandemic; is it easier to convey this “big data” in media when it doesn’t have an emotional, or human centered connection? I’m curious what my project group and the rest of the class thinks about this.
Matthew Gancayco, October 23, 2020
Post-productionFor my post this week I wanted to focus on the question that was asked in class, which was the how do the measurements of data shape the realities that they measure, and what are examples of this phenomenon. The example given in the text is economic measurement tools. The ability to quantify and interpret big data in the economy shape the reality. Discovering the patterns and mechanisms give the entity meaning that we were unaware of. This phenomenon reminds me of the proverb, “If a tree falls in the woods, and no one is there to hear it, does it make a sound.” Does the awareness of the meaning behinds big data equal it’s existence? Does the data not exist without the ability to understand it?
The measurements shape the reality by opening our eyes to it’s existence, but does it shape it in another way? In the case of a mechanism that can be easily swayed by analytics, such as the stock market, does Big data shape the reality by changing people’s feelings toward it? When patterns and trends that imply a dip in the market is coming, people often will sell their equity thus fulfilling the prophecy. On page 675 it asks “But we do think there are serious and wide-ranging implications for the operationalization of Big Data, and what it will mean for future research agendas. As Suchman (2011) observes, via Levi Strauss, ‘we are our tools’. We should consider how the tools participate in shaping the world with us as we use them.” Big data is used to analyze patterns, but can also cause patterns, so it is important to be weary of it’s use.
Zack Kurtovich, October 22, 2020
Post-productionThis week, I was truly impacted by Professor Himpele’s use of the Beatle’s vinyl records as an analogy to “drop the bottom out of the idea of authenticity” and our short conversation surrounding the blurring boundaries between reality and representation. As Professor Himpele explained in class, mp3 recordings are endless layers of representation, which points to the inexistence of a “true”, “authentic” reality. For me, that brief moment represented the culmination of weeks of reading and discussion, making it one of the most salient points of this course to date. I found that this discovery challenged my understanding of authenticity as a standard for a message’s successful communication, a conceptualization that I had been relying on since I was a child. When I was in the 5th grade, my favorite band was the Beatles, and for Christmas I asked my parents for a digital copy of the Magical Mystery Tour on iTunes. Almost insulted by the notion, they insisted that I listen to a more “authentic” medium to capture the true essence of the artist’s message. They eagerly gifted me with an entire collection of the Beatles’ work on cassette. While I sincerely appreciated the gesture, we didn’t own a tape player, so I never got a chance to listen to them. That said, it impressed upon me a lingering respect for the material world rooted in this conception of authenticity’s superiority, which I’ve carried for years…. or at least until Tuesday’s class. After Professor Himpele demarcated the seams of authenticity and exposed it as a bottomless pit, I’ve had to wrestle with and dismantle this unwitting and ultimately irrational commitment to nostalgia. I’ve had to come to terms with the fact that the original is not always better. With the very idea of originality called into question, why even consider as a factor when forming an opinion? The mp3 technology’s capacity to provoke these sort of insights and questions is exactly why mp3s, and the Napster era it emerged from, were met with such fear and anxiety by members of the copyright community. In light of this revelation, the notion of ownership seems irrelevant: after all, with this underlying conceptualization of authenticity stripped away, it doesn’t matter who was first, only who was better. As a digital native raised by the Internet, I find it easy to accept this, as I’ve already been indoctrinated by digital realms where intellectual property protection is practically non-existent. That said, I think there’s something to be said for the visceral connection one feels while listening to live music. If the goal of music, and transitively of media in general, is simply to communicate the artist’s message in a way that it evokes its intended emotional response, then mp3s succeed. However, on some level, I still believe that there must be representations that are closer to the essence of original message than others, although I am no longer convinced that it matters. What do you guys think? Is our love of concerts rooted in the “authenticity” of the message or the social context they provide? I am looking forward to dissecting this issue more in class!
Maya Stepansky, October 22, 2020
Post-productionWhat stuck out to me most about the reading on Big Data by Boyd and Crawford, was the assertion that big data is not just narrowed down to ones and zeroes, but rather that it is subjective, involving interpretation to shape and organize it into logical sets. And once it is produced, it requires more interpretation to analyze it, given its context. This makes me think, then what about big data (or data in general) is actually objective? When it is in it’s raw form, can we then say that the data is objective? I would assume that there involves a collection process of the raw data by a researcher. To begin to make data sets, a researcher has to know what raw data to chose from. Doesn’t the researcher’s process of collecting raw data then require another layer of interpretation? Does this therefore imply subjectivity even when it comes to raw data? Then what about it is actually “raw” if it was a set of data that was interpreted and narrowed down (just like Big Data) in to a “set of raw data to further group into sets of Big Data”. I think that that the term “Big” automatically implies a categorization of a certain type of data which has been distinguished (as distinctly different from other types of data), interpreted, and narrowed down from other types of data–this categorization implies that it was interpreted at some point, implying its natural subjectivity. Then again I ponder the question, what is actually objective about data? I’ve always assumed that that data was objective, so there has to be somethingobjective about it. Possibly, objectivity only exists in the initial record of the singular statistic, such as when a person runs a mile and their exact time is recorded. But once there is a mass of data and the sorting and interpretation begins, then we see the notion of the subjectivity of data coming to light.
Jerome Desrosiers, October 22, 2020
Post-productionFor this week’s post, I want to keep the conversation we started in class today when I briefly mentioned patterns and when Lauren asked “what or who counts as a person?” The big data isn’t only about the big data but what social media companies can assume when analyzing that big data. When we go online and surf the web, we create that data that companies can pick out certain patterns. For example, my phone knows that I usually eat pizza once every month which happens in the first week of every month. That means that pizza restaurants can use that data and pattern to make sure I get a Dominos advertisement on every social media at the right time.
The problem that I struggle with is brought up in Boyd and Crawford’s: “Too often, Big Data enables the practice of apophenia: seeing patterns where none actually exist, simply because enormous quantities of data can offer connections that radiate in all directions.”(668) This made me think that the large number of data can lead to wrong assumptions of the users which pushes me to think that data can never represent accurately its users. That data has to be interpreted which means it can also be misinterpreted and it has limitations. The reality of it is that the data doesn’t care if you are a person or not and it will never completely represent someone.
Rei Zhang, October 22, 2020
Post-productionI want to consider the question raised and answered by boyd and Crawford on page 666: “Do numbers speak for themselves? We believe the answer is ‘no’” and link it to their second point, that claims to objectivity that come with Big Data are misleading.
People are always going to need words and description to write about data. Data needs to be graphed, labeled, and plotted; figures need captions and descriptions to let the audience know what “truth” to take from the numbers. If the numbers speak for themselves, then why does anyone even bother writing research papers? Just give the numbers and have everyone draw the “true conclusion” from the data.
Numbers always require a description and thus a context to give them meaning. -2 (arguably raw data) without a description is useless – is it the change in temperature, the drop in stock points, the velocity of a bird? Because of this requirement for a description, data is never objective. When deciding what data to collect, you describe and categorize what you’re looking for, already shaping the outcome of the dataset and the conclusions you’re able to draw. Then, in processing, even more layers of interpretation are heaped on to “raw” numbers; researchers prune away numbers and data that they don’t want in search of some true pattern. Arguably, the most crucial step in data science is the step of data cleaning – you’re shaping the final result irrevocably by choosing what to keep and what to discard. Most people, however, fail to realize how crucial and important pruning and cleaning are to data analysis; the attention is on the final, “objective” results, not on the critical work done in the filtering steps.
Layers of meaning always need to be attached to numbers through words and by people, and this is no different for big data; the unique and dangerous thing about big data is that it attempts to obscure just how interpretive it really is.
Grace Logan, October 16, 2020
Post-productionFrom this week’s reading, the paragraph that goes “To spell out this…site of retained authenticity” (p. 13), touches on several significant ideas that I have seen come up in this class and other anthropology classes. The first sentence claims that study of the digital world has potential to inform us of the “mediated and framed nature of the nondigital world”. To me this seems like another iteration of studying something to learn more about its opposite. I phrased that in an intentionally reductive way, as I am seeing that often there is more nuance to be revealed about these two objects/terms/concepts that make it so they can no longer be considered opposites. I am thinking back to Mitchell’s discussion of how attempting to define the Orient could reveal more about how the Europeans define themselves. (And in class yesterday, this came up again when we talked about what words come to mind when we hear “digital” and sometimes a concept can be defined by considering what it is not.) As we discussed before, Mitchell comes to the conclusion that these categories are not opposite and calls attention to the harm done in viewing them that way. In a previous post, I had written about this and how it relates to authenticity. I can see parallels to this post and how Miller and Horst compare the virtual and its implied opposite, the real. In particular, the last sentence they say that “fetishizing the predigital culture as a site of retained authenticity” would undermine the efforts of digital anthropology. I think this echoes the consequences of the Orientalist view that a previous iteration of a culture, perhaps before the exposure to “western” technologies, is more authentic.
After thinking about this, I am very hesitant to consider things as opposite to one another. I am also now thinking about the relationship between “authentic” and “real”, I know outside of ethnographic contexts “authenticating” something means to determine whether or not it is “real”. But, I now wonder if in the context of ethnography we conflate these terms. At the end of my post I had referred to earlier, I stated that authenticity should be defined by oneself, and I think that for the most part I consider this to be true for what is “real” too, at least when doing anthropology. Maybe what I am really talking about is relativism, but I think that it is more insightful to try and understand what one considers to be real rather than get caught up in if I think that it is real. I also wonder why, when considering what is real and authentic, we have a tendency to glorify the past.
Emily Yu, October 16, 2020
Post-production“So today, we still find that most people prefer to resort to blame and assume there is human intentionality behind the negative side of these digital coins…digital technology is dialectical and intrinsically contradictory; often what adjudicate as its good and bad implications are inseparable consequences of the same developments (24)”
I wanted to point to an example of what this quote is trying to illustrate in our lives (I was almost going to say real lives but then realized that this was the authenticity trap). I recently watched a movie called The Social Dilemma, a movie critiquing the ways in which the algorithms behind huge tech platforms (i.e. Facebook, Google, etc.) are tweaking and changing in response to our interactions with our screens. For example, the same two people using Facebook will have very different home screens that are catered to their specific interests; entering into the Google search bar the same word (i.e. “election”) will yield to suggested autocompletions based on your past search history. Here is a clear example of digital technology being dialectical and intrinsically contradictory: using the same development (algorithms), these platforms have personalized and tailored our technologies to reflect our needs/wants (the positive) but at the same time will only reinforce our own concepts and understandings of the world, thus creating an echo chamber that has consequently led to a lot of polarization (i.e. elections) and potential disinformation (the negative). It might be easy to blame the technologies themselves, but perhaps the real blame should be looked at ourselves and the ways that we have created and reinforced our own cultural systems into these technologies.
The idea that digital technologies are merely just shaped into reflections of ourselves and thus our cultures reminds me of Geertz: “man is an animal suspended in webs of significance he himself has spun.” The digital lives we have created are very much webs that we have spun ourselves through the ways that we have interacted with our technologies. Thus, I would agree that (1) ethnography will still play a significant role in understanding what it is that makes us human and (2) perhaps the interpretation of the symbols in our digital lives will be made easier as digital technology given the fact that we must reduce a lot of qualitative aspects of non-digital lives into quantifiable symbols (i.e. hearts, search bar, etc.).
Jerome Desrosiers, October 15, 2020
Post-productionAfter today’s class and discussion, I really want to dive back in this idea of prosumer and prosumption that we briefly went over. In short, prosumption is when the line between content producer and content consumer becomes blurry and they become one. This is clearly something that we have all experience especially with the rise of social media but also other services like Ebay or youtube. Interestingly, social media is one of the many words that came to my mind when Professor Himpele asked the class the first word we thought of when hearing “digital”. I feel like it the digital has become such a big part of our lives that I have a hard time imaging a world without it. Now, People can develop relationships by connecting solely digitally, digital media has changed the way political campaigns are ran and even school courses have moved to online.
We have previously talked about authenticity and this made me think about a similar question and it goes along similar topics that Maya brings in her post-production post. I wonder if authenticity can be achieved digitally? Are we less, just as or more authentic online and through digital media? Maybe digital allows us to be less authentic or have a better control on our authenticity. I know this is a loaded question but I think it was worth bringing up to you guys.
Maya Stepansky, October 15, 2020
Post-productionAs we discussed the digital today and I brought up the point about feeling as though internet/social media use began to appear as a disguise for reality since it was the only form of social interaction during the pandemic, I began to think whether or not that sentiment could actually be deemed truthful in years to come. With all of the exponentially increased use of technology throughout the past few decades, I think that the digital has seeped further and further into our realities. Dystopian movies such as Wally or futuristic episodes in shows like Black Mirror make me ponder whether the digital can actually be an addition or even a replacement of our reality (though the latter is quite unfathomable). Additionally, when I think about how most jobs going remote during the pandemic has made companies realize that they are better off keeping their employees working online (even after the pandemic), I begin to think that the digital may dominate our lives in the future in more ways than we thought possible. Though things will likely go back to “normal” (whatever that term means anymore) in a few months/years as the pandemic dies out and people begin to interact more in person, who is to say that there won’t be other lingering digital effects in addition to an increase in online jobs? So at what point does “reality” apply to the “digital”? Are these two terms always mutually exclusive? I know that there is digital that exists within our realities, but can reality ever exist in the digital? Does it already? Will it ever? All of this makes me really think, then how can/should we even define the term reality? I think that these are all questions that are definitely worth thinking about.
Rei Zhang, October 15, 2020
Post-productionThis topic, the digital and culture, and our class discussion immediately reminded me of a New York Times article I had read three days ago (it turns out Prof H actually linked it earlier in Slack), describing a group of researchers who use tweets to measure the emotional state of people globally. The researchers are using the digital (algorithms, computing) to measure social attributes that are more intangible. (While “intangible” was associated with the digital in class today, I would argue that many social interactions are intangible in a different way than the digital. For example, emotions and tone are notoriously hard to convey over texts or the internet.)
There are tons of interesting ideas and connections here to the Miller Digital Anthropology and other previous readings. The author says that “Without our normal social life as antidote and anchor, our social media now feels more like real life than ever before”, which is the sentiment that Maya echoed today. There’s the issue of the cultural context of language usage; the researchers have only looked at English so far, so what sentiments would be expressed in spaces that use other languages? There’s the idea of cultural context and how that changes, which comes up with discussion of the increased use of swear words (and subsequent decoupling with intense emotion). There’s also a connection here to the illusion of truth and fidelity – the researchers present May 31st, 2020, as the saddest day on record, but is their algorithm an accurate measure of mood? The truthfulness here is reinforced through citing the amount of data, and the look at the collective.
Interestingly, the article also presents a way to use these collective data analysis findings and re-apply them to the individual, for example, looking for signs of post-partum depression in tweets of individual mothers. This example presents a way to merge the concepts of “thick description” (big data in the sense of tons of individual big data) with the more numerical concept of digital big data.
Article link again: https://www.nytimes.com/2020/10/12/style/self-care/social-media-.html
Jeffrey Himpele 
Zack Kurtovich
Comments
Grace, this post ties together very nicely the relationships between interpretation-representation-data in your concise statement that “data is a social fact and is socially produced.” Thus update to your visualization as a web definitely helps make sense of the inherent multiplicity of social perspectives on data that your group discussed.