Building off of previous observations from Drew Gill, I decided to track class participation based on outfit. I recorded what each person in class wore for their shirt and their pants. Shirts were divided into four categories: Short-sleeve/T-shirt, Polo, Button-Down, and Long-Sleeve/Sweatshirt. Pants were also divided into four categories: Shorts/Skirts, Khakis, Jeans/Other, and Sweatpants. These categories were designed to be a bit vague, mainly because men’s and women’s apparel can vary quite a bit in certain situations.
Proportions seem to align, more or less. The largest percentage disparities have been bolded and changed to red. On Thursday, March 26th, Jeans/Other underperformed when it came to participation in class, accounting for 25% of the number of people in class, but only 9% of the participation. There were other large disparities as well, but that specific one was the largest.
Ann Helen Petersen, in “Big Mother Is Watching You”, her article from BuzzFeed.com, highlights the rising wave of wearable tracking devices. She describes in detail, many of the new types of wearables, ranging from a simple pedometer that can track an individual’s steps throughout a day, to a type of wearable that records information while attached to a person’s dog. She also writes about some of the conversations that she had with many individuals.
By the end of her article, Petersen narrows in on the point that “the future will be quantified.” Already, many (including some individuals who have already posted on this blog) have wondered if this quantification of the future is a good idea. Should we allow our lives to controlled by machines on our wrists and in our pockets? At what point should we stop? What parts of our health, and in general, our daily lives, should we control?
“That promise of ultimate, seamless simplicity — and the happiness that supposedly accompanies it — will be too much, even for the most suspicious and privacy-conscious among us, to resist.”
At what point do we trade the loss in privacy for the seamless simplicity, and more importantly, the happiness? Presented with these facts, would we not trade a small bit of privacy for a cure to diseases like diabetes and cancer? Do we relinquish our individual information if it can help the greater good? It is possible then, that we could even be trading our idea of reality, a reality run by our own minds, for a reality run by machines, while significantly progressing our understanding of human health in the process. Is this a fair trade? That is the choice we all are going to have to make.
On Tuesday and Thursday of this week, I decided to observe some of the patterns of sickness that seem to be sweeping the campus this time of year. Over the length of each class (and the few minutes I was in the room before and after class), I recorded how many times I heard someone in the class:
Clear his/her throat
Say the word “flu”
Say the word “cold”
Say the word “sick”
From the data below, we can see a few trends. One obvious trend is that the all “sickness-related actions” seem to decrease on Thursday. However, some of this data could be skewed, because of the fishbowl discussion. I did spend some time in the fishbowl, and I was not able to track these behaviors as closely as I hoped during that time. Even so, it seemed to me that the prevalence of “sickness-related actions” did indeed decrease during Thursday’s class.
Lauren F. Klein, in her analysis of Thomas Jefferson and his data-storing tactics, The Image of Absence, comments on multiple ideas regarding the collection and interpretation of data. The most prominent idea featured in Klein’s work is the idea of “archival silence,” an idea that can simply be defined as “gaps in an archival record.” Though Jefferson was meticulous in his record-keeping, he would also reduce mounds of data regarding his slaves into small bits. Klein uses a particular slave of Jefferson, James Hemings, as an example, saying “Jefferson himself was at times required to recognize, if not to redress, the flawed logic that reduced Hemings’s life to a line of data.” Klein views this particular lack of record-keeping by Jefferson as an unfortunate sign of the times, showing that Jefferson played a large role in the silencing and subjugation of African-American slaves.
At the same time, Klein presents the reader with ways to combat the problem of “archival silence,” saying the reader ought to “look to the pathways of connection between persons and among groups.” Klein then presents a graphic showing the patterns of correspondence between Jefferson and others, concerning James Hemings. This graphic is not unlike those presented by Micki Kaufmen and the “Quantifying Kissinger” Team. Both graphics attempt to piece together information that is not explicitly presented in the data collected and attempt to display patterns, or “presences” (as described by Stephen Best and Sharon Marcus), hidden within the data collected.
It is this uncovering of “archival silence” that seems to scare so many individuals today. Many Americans will not soon forget the Edward Snowden scandal, nor the subsequent report that showed the US government was in possession of millions of Americans’ phone records. Why did this scare so many people? Was it because people were afraid that the US Government knew who we were calling each and every day? The could be. But, maybe what is more important is what phone records don’t explicitly show. Maybe, by using Klein’s tactics to uncover archival silence, and by reading the patterns and “presences” within these phone calls, the US government can ascertain more information about the callers than is ever presented within the records themselves. Maybe what citizens have to fear most is not the uncovering of their data, but the patterns hidden behind that very data trail.