Group 2 – Page 2 – Data Culture

Taking Control of Big Brother’s Eye

Consumers control the market and ultimately have the power to limit the sight of “Big Brother’s eye”

I found Peterson’s title and reference to George Orwell’s 1984 both comical and clichéd. The reference to “Big Brother” is so commonly used when referring to big data because it is easily assumed that any corporation or government organization with hands on the data would automatically and instantly abuse the privilege and spy on the population. It is rarely realized that such a freedom is in fact a privilege and not a right. If us, as consumers, were so interested in privacy, we wouldn’t demand such tools.

Why is it that our Jawbone, Fitbit, Misfit, or whatever other device we use to track exercise and sleep HAS to link up with our iPhone? Obviously, the answer is shear convenience. How appealing would it be to download all of your daily data to a laptop or some other form of offline tracker? That would seem monotonous and excessive. Developers have found a way to incorporate something useful, a fitness and sleep tracker, and pair that with the thing that Americans interact with more than anything else on a daily basis, a smartphone.

All inventions come to improve or initiate efficiency in a particular activity. That is simply the nature of technology. Pederson’s idea of augmented memory also sounds extremely convenient (and dangerous, but that’s another conversation). Having the ability to remember everything I ever read, studied, or discussed would come with so many advantages. However, the fact that that information could be digitized and distribute would also frighten me. Again, such an invention would still only be optional in society, which is the beauty of a market economy. Unlike in Orwell’s dystopian society, we can control Big Brother’s market if we really desire. Unfortunately for those fearful of Big Brother’s eye, millions of fitness tracking users would agree that convenience is extremely important, thus fueling the spread of these big data mechanisms.

The Choice We All Must Make

Should we give up our private data in order to progress our understanding of human health?

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.

The Self in the Quantified Self Movement

Anne Helen Peterson in her piece titled Big Mother is Watching You discusses the current and future implications of self-tracking wearables on our daily lives. By 2018 with over 60 million fitness trackers in use worldwide we will see the explosion of self-tracking devices. With the release of the Apple Watch we can see how self-tracking devices are transitioning into our mainstream day to day culture.. But, how will self-tracking change the way we live our lives? While self-tracking will empower individuals to improve their health and to discover things such as eczema inducers, self-tracking will also peel back the mystery of the human body. We will be able to quantify information that before was merely qualitative. For instance, instead of having the qualitative feeling that you had a good nights sleep we will be reliant on data from an app which will quantify the quality of our sleep based on our movements and breathing patterns. In a way this is excites me, but more often than not when I ponder these implications I feel as if this will undermine the importance of human emotion and feeling. Instead of deciding what feels best to us as individuals we will be reliant on what an app says is ideal for us. This reminds me of a current trend in medicine, which is the transition towards personalized medicine. In my opinion only when Quantified data is matched with our qualitative human emotions will I feel satisfied by the conclusions of self-tracking devices. If we allow it, self-tracking could easily strip us of our individuality and will undermine and doubt our own feelings about our bodies.

Transforming Experience Into Statistics

Ann Helen Petersen , in her article “Big Mother Is Watching You”, describes the prominence that wearable tracking devices has gained, and the reasons behind this sudden change. She discusses the fact that companies are attempting to gather data about people in order to “improve” their lives. This improvement will be bought on by the fact that users wearing the devices will be able to analyze themselves in ways that they could not before. These people now have the power to dissect their own lives, and in a certain way have more control over their experiences. While I agree that the new wave of wearable technology does empower the user to a certain extent, I would like to propose the viewpoint that this technology is a two-sided sword.

The good comes from the empowerment. It is a great thing to be able to self test your urine to make sure that you are healthy, or to check up on your hear rate to make sure that you are not in danger of a heart attack. These are benefits that wearable technology provide. Our lives are made easier through the MimoBaby that allows the parents to maximize their child caring methods, while allowing the more tired parent to sleep more. It is beneficial to measure bodily food intakes and monitor weight among things, if one wishes to keep a healthy lifestyle. The purpose of wearable technology is good. The negative aspects come into play when one talks about the specific numbers themselves rather than their purposes.

Running

While people are able to monitor their lives and check all the statistics of their day, they begin to pay more attention to these numbers, than the actions that they are doing. In our high-tech society , many people are constantly on their phones, and data-tracking gives them more of a reason to check their screens. I believe that we as a society will get to a certain point where we no longer perform activity simply for the pleasure of it/because we want to, rather because we feel the need to live up to the numbers that we are being shown. It is a possibility that parents will feed their child simply because a machine is telling them to, not because the parent has developed a bond that allows them to predict baby needs. Some may run and have a great time running, but will not get the full experience if they are solely worried about the numbers of the run. These statistics have the power to put the user in a certain mindset where numbers are the only important thing. I do not wish to sound apocalyptic in any way, but it is imperative that we consider how full disclosure of our life experience will affect our overall life experience . We need uncertainty in our lives; that is how we learn best. If one knew exactly what was going to happen in one’s life, would it be as much fun? This question can be applied here. Petersen agrees that the ability to rely on ourselves for better life improvement makes us feel more alive than relying on an app. Wearable technology does have benefits, but we must not let statistics distract us from living.

Beware of the Wearable Devices

In her article “Big Mother Is Watching You,” Anne Helen Petersen discusses the recent rise in popularity of wearable data tracking devices. Petersen highlights devices that run the gamut in terms of functionality, ranging form the mundane fitness tracker to devices made for children to track their elderly parents’ household routines. Within the article, Petersen also hints at how her own fitness tracker use has affected, and potentially influenced her behavior. She notes that she has become obsessed with her sleeping data, and that she even purposefully excludes certain nights from her data collection, so as not to ruin her nightly averages.

Later in the article, Petersen discusses the potential effects that fitness trackers and other wearable devices may have on the insurance and medical fields. Specifically, she speculates that if wearable devices become more sophisticated, they may be able to help identify certain medical conditions, thereby reducing the number of trips to a physician’s office. Wearable health trackers, pending some technological innovations, have the potential to eliminate the knowledge divide between the general public and highly-educated doctors. While it may be years before these innovations are in place, they would certainly impact the insurance industry as an individual’s riskiness could be more accurately calculated using their accumulated data.

While purposefully altering one’s own sleep data and the potential health industry changes associated with fitness trackers may not seem related at first, there do exist some important interactions between the two. The first effect that comes to mind is the placebo effect that could exist simply from wearing a fitness tracker. It is likely that someone who is constantly reminded of their physical activity will workout more and generally be more health-conscious. While this encourages healthy behavior, it may occur even when the their fitness tracker is not working properly. For example, even when the R65 application was down, I found myself feeling guilty for everyday that I didn’t work out, despite the fact that any exercise I got wouldn’t be recording anyway. Additionally, health trackers pose a potentially adverse effect on the insurance industry. If customer’s data is being mined for insurance purposes, then someone who artificially alters their data has the ability make themselves appear as a less risky investment than they truly are. With the rise of fitness trackers and the overall quantified self movement gaining traction, the consequences of our daily data become increasingly more interesting and controversial. While “forgetting” to wear our bands when we go to sleep may seem harmless now, this could become a real problem if fitness trackers continue their rise in prevalence in our daily lives.

Inaccuracy of Maps

In class the other day we were told to draw maps around campus to other places that we may or may not have known the location. After thinking about the drawings that were made and talking about how different maps could be inaccurate. I wanted to see what different ways in which a map could be inaccurate. So as I was looking on the internet I came across a study done by Colorado University at Boulder looking at the different types of inaccuracies that can be found in maps. The article, “Error, Accuracy, and Precision” talks about “the problems caused by error, inaccuracy, and imprecision in spatial datasets.” Throughout the article it talks about the different inaccuracies. The different types that they bring up are format of the data, age of the data, relevance, density of observations, map scales which all deal with the characteristics of the map itself. It also goes over inaccuracies made through general error such as numerical error and analyzing the data gathered. It was interesting to see the different types of inaccuracies, and it goes with the notion that was brought up in class stating that all maps have errors and are inaccurate.

Questions are constantly brought up about how to make maps more accurate. The article raises some of these questions. How accurate are positional and attribute features? What projection, coordinate system, and datum were used in maps? These are just two of the many questions that can be asked on how to make maps more accurate. What can cartographers do to make sure their maps are as accurate as possible? What are the most important aspects of a map that need to be the most accurate in order for amble data to be taken from it?

A Mercator Mapping Mystery

After our discussion Tuesday, I began to do some research on my own. While searching for some interactive inaccurate maps, I found a blog that boldly declared to me that every map I had ever seen was radically wrong. The blogger began to explain that one of his co-workers mentioned a thing to him called the Mercator project. Being unfamiliar with the term, as was I, the blogger browsed the term “Mercator.”

As Cam Bard previously noted during his discussion, it is impossible to represent a three dimensional world on a two dimensional scale. Apparently, a cartographer from the 1500s named Gerard Mercator created the ovular map that we recognize today. In an attempt to preserve the shapes of the world’s countries, Mercator drew the countries as we commonly see them on the map. However, he did not account for the scaling with relation to the Equator. On most maps, countries and landforms appear larger and larger as they are placed farther from Equator. The blogger’s primary example was Greenland. The point was made that Greenland is roughly 60% smaller than we believe it to be according to modern maps.

A Mercator Puzzle was created to show how warped depictions are on most maps. It was quite intriguing to find that, according to the Mercator Puzzle, Greenland was roughly the size of the Democratic Republic of Congo (an average-sized country in the middle of Africa). The thing that stuck me after investigating the Mercator mystery was, how can the people who designed the Mercator Puzzle be so sure that their map predictions are accurate??

The Role of the Cartographer and the daily map user

In response to cabard’s post, I believe that he has a very good logical standpoint on who gets to decide what goes on maps, but I feel like he downplays the role of the user. He states that it is up to cartographer to decide what goes on maps, and how truthful that information is. I believe that while the cartographer does have this power, those who utilize the services have power as well. If a particular person wishes to have something on a map, then they should be able to suggest this to the cartographer. Since this information is for the users, then the users should be the people kept in mind when creating maps. These people can band together to get a say in what they believe to be most important for representation purposes. Regarding the point made about getting the bigger picture but losing the details, I believe that this does not always have to be true. While the little bits of information can be lost, this can be prevented if we decided what the little bits information are. If a map wishes to have information regarding the local area, then the little information will not be relevant as the overall purpose is to graph a small area. Once again, the user should decide what the purpose is, so if they wish to have a big area mapped then they must be conscious that certain details will be left out. If they want small, details should not be left out. Finally, I agree with the point that we can have either distances or shapes, but i do not believe that this will be a problem for much longer. With the increasing amount of technology in our surroundings, soon we will be able to bridge the gap that has been established. It would be crazy to think that this issue regarding maps will be a problem in the future.

Scaling: How Map Makers Make Mistakes

In the discussion following Tuesday’s map making exercise, which required us to create three maps leading from Studio D to Nummit, Davidson Pizza Company, and Chipotle, a number of people mentioned how they had difficulty managing the scale of their maps. I encountered this scaling issue when I ran out of space while attempting to draw the path from Studio D to Nummit. Despite the distance between the two points amounting to only a few hundred yards and the fact that I make this walk on a daily basis, the other two maps that I drew were far more accurate. While I am clearly a terrible cartographer, I believe that my familiarity with the path from Studio D to Nummit actually hindered my ability to successfully depict the route. Because I know the route so well, I found myself trying to add every little detail to the map that I fit, and as a result, I had to drastically alter the scale on the map to fit Nummit on the page. Conversely, when drawing the other two maps, I had far better spacing and was able to fairly accurately show how to get from one place to the other. I believe this was the case as I was not as concerned with drawing every minute detail, but instead I focused more showing the route from point A to point B.

While others may not have had similar experiences drawing their maps, mine left me asking if too much information can be a detriment when constructing a map. Ultimately, this question relates to Monmonier’s article and highlights the tradeoff between accuracy and usefulness that all map makers face. I found through this exercise that the more information one tries to incorporate into a map, more difficult it becomes to use the map. On the other hand, too little information appearing on a map is potentially dangerous as the omission of an important detail could render a map completely ineffective.

Observations

Tuesday:

15 open computers on desks

1 hat

3 girls no hats or headbands

Moved multiple times during class

Forced participation

Thursday:

25 open computers on desks

3 hats

3 girls 2 headbands no hats

Stationary during class except to get fit bits

R65 Skype call

0 people making eye contact with R65 camera

Voluntary participation