The Quantified Self

Day 1, Nov 22 – Prior choosing to measure my screen time I hadn’t actually ever taken the time to check for myself. As my experiment would follow I checked my phone’s screen time option in order to tell how long I used my phone on that day. Upon checking the first day, to my suprise, my screen time was calculated at six hours and 43 minutes. This surprised me as I would’ve never imagined that I would be on my phone almost 7 hours out of the day. 

 

Day 2, Nov 23 – Despite having somewhat of a disappointing screen time the day before I was quite proud of today’s data. Cutting my past screen time by two hours I only spent four hours and 53 minutes on my phone today.  I’ve also found a tool that tells you how much time you’ve spent on certain apps. It appears most of my screen time is spent on social media and entertainment apps.  

 

Day 3, Nov 24 – Overall, l definitely wouldn’t mark today’s screen time as improvement. Ultimately my screen time was found to be at nine hours and 45 minutes. While some of this may be mainly caused due to being in the car for three hours this is still definitely alarming. On a separate note, I’ve begun to find it increasingly more noticeable when I take my phone out to use it, rather than before when it was a subconscious act. 

 

Day 4, Nov 25 – While I also wasn’t the busiest today, I found that I had made a major improvement in comparison to yesterday’s screen time. At the end of the day I found my screen time to be only four hours and 23 minutes. I’m currently in Long Island at a family member’s house spending time with my siblings and family. I’ve also watched a good amount of movies which may explain the low amount of screen time.  

 

Day 5, Nov 26 – I’ve been pretty occupied today going on walks and spending time with family for Thanksgiving. At the end of the day I found my screen time to be at five hours and 19 minutes. I found that a lot of this time came from some of the music apps I use which may have had an effect during my time driving, and not actually being on my phone. Regardless, I still found 5 hours and 19 minutes to be a satisfying amount of screen time. 

 

Day 6, Nov 27 – Today I drove home from Long Island, which is a three hours drive. As you may recall from day 3, the last time I had taken this drive, my screen time was reported at nine hours and 45 minutes. However, this time I slept during most of the car ride and it made all the difference. At the end of the day my screen time was four hours and 26 minutes. Being in similar circumstances to a time when my screen time was at its most high I was able to cut my screen time in half. 

 

Day 7, Nov 28 – While most of my day revolved around preparing for my brother’s confirmation, I still made some room for my phone. At the end of the day, and after a two hour confirmation, my screen time was reportedly calculated at four hours and 46 minutes. After finding my screen time to be close to seven hours, on day 1, I felt very compelled to limit my phone usage. After reaching multiple days having under, or close to, five hours of screen time, I feel very accomplished. I’ve also found that screen time when using social media apps is still the single greatest factor while entertainment has decreased exponentially, which now may be something to consider. 

 

Lukas Comerico

The Quantified Self

 

Upon deciding to pursue an interest in the quantified self, and doing some background research, I found that while the quantified self is an overthought term it is far more simple in nature. By definition the quantified self completed is “the act of using personal data to improve one’s quality of life.” In other words, the quantified self involves those who pursue tracking their personal data, mostly through technology, in attempt to better themselves. Overall, the qualified self ties with simply looking at your life and finding things you want to change, however, through data collective and analysis. Hypothetically, if an individual recently became unsatisfied with their calorie intake then the quantified self is a very helpful strategy. For example, after each meal or day of eating the individual is able to calculate exactly how many calories they’ve consumed. Whether this is done manually or through use of an easier calorie measuring tool, like a fitbit, that individual should be able to pick out eating patterns in which they would like to fix. Through analyzing eating patterns over a series of days, an individual should be more immersed in their calorie intake than ever before, moreover being able to see the specific problem and act on it. Through the quantified self, by directly focusing on one or more certain aspects of your life and realizing how these aspects affect you, it becomes far easier to willingly make better choices about your life when dealing with those aspects. 

 

After first looking over the project prompts I already found that I had a major interest in the quantified self. While this may be because one of the biggest takeaways was a sense of self improvement, I also found the concept to be intriguing and interesting. While the importance of self improvement will most likely vary from person to person I’ve always found myself to be strong at building upon myself and for myself. As a result, for my project I choose to analyze the amount of screen time I spent on my phone daily, throughout one week. Another reason I choose to measure my screen time is because I actually never had before and was very eager to learn how much time I spent on my phone per day. 

 

My overall goal through my project was to calculate an average amount of hours I spend on my phone per day and limit that to an amount that I’m satisfied with. I found this to be the most important because I assume this is something almost everyone my age thinks about. In an age where everything is being digitized it should still be just as important to witness the real world and not be constantly drawn to our phones.

 

In order to gather data and analyze my daily screen time I used a tool that apple offers freely. Within settings I found an area called screen time on my Iphone, that anyone with an apple should have free access to. Here I found that an amount calculated in hours and minutes measured by screen time every single day. This would allow me to figure out exactly how long I used my phone on a given day and specifically at what time during the day. I found this extremely useful as when I would go back at the end of the day I would remember certain circumstances where I remembered using my phone for specific instances. I found knowing that I used my phone for a specific and useful reason reassuring because that meant I wasn’t wasting my time looking at something useless. On the third day however I was enlightened to another option that I found to be even more beneficial. By looking at your daily screen time and scrolling down a tiny bit I was able to see how long I had spent using certain apps. I found this extremely beneficial because then I was able to tell what specific apps I was overusing rather than just knowing I was overusing my phone in general. 

Words Cited

 

Peters, Katelyn. “Quantified Self.” Investopedia, Investopedia, 26 Sept. 2020, www.investopedia.com/terms/q/quantified-self.asp. 

 

The Quantified Self

Day 1

Today was my first day back at home. Already, my watch connected to the GPS signals and could tell where I was. Apparently, I slept well in my bed at home. This image is a screenshot from the Garmin App. Today I discovered it tracks your movement every hour. I find that really creepy, and it is not something they advertise. I think it is good to bring awareness to the fact technology can do things you are unaware of. 

Day 2

This is my second day back home. The data is very similar from yesterday. However, I ran in a different place. To protect your privacy, Garmin only records the county you run in. However, one can still see exactly where you run through the app. I think this feature may give users a false sense of security. The constant monitoring of my heart rate throughout the day is starting to creep me out. 

Day 3

Today my resting heart rate was lower which is good, but I think it’s because I ran less. I like that the app can help me improve my recovery with the heart rate feature. One way you can take back technology is by not wearing or using it. I took my watch off to charge and I like that there is no recorded data.

Day 4

A cool thing I discovered today were the seasonal themed challenges on the app. I think that is fun and enticing. One thing that irritates me with the app is how slow it is to connect and upload data from my watch. I think it may be because of the amount of data my watch holds, which is again, creepy. 

Day 5

I am starting to get freaked out about the steps and timing the app constantly records. By looking at this data, someone could find out when I am not home and rob my house. It is hard to weigh out the good and the bad with surveillance. 

Day 6

Yesterday I went up to visit my friend in Pittsburgh so that threw off my sleep and running schedules. It may be good to have that variety so no one can constantly track you. A good privacy feature of the app is that unless I record an activity, it doesn’t display location. From this data, you can not tell I left home. 

Day 7

Today was an interesting day. My watch did not connect to my phone’s bluetooth so a lot of the data is missing. I like that this is another way to control my data. Additionally, you can see I ran in a different area than usual. This is interesting because Herndon is a part of Fairfax County so the data is seemingly randomly more precise.

Quantified Self Reflection

My project followed my daily activities. I utilized a Garmin Forerunner watch (worn 24/7) as well as the Garmin Connect app. Initially, I tried to use the app Instant, but I found it far too invasive upon my data. Through the Garmin Connect app, I was able to gather data such as sleep, steps, activities, and heart rate. The data was displayed as totals as well as broken down hourly. Each day I synced my watch and took a screenshot of the previous day’s data. I reflected upon the data in my Data Diary. Tracking my daily data raised questions of privacy for me. 

The quantified self is a relatively new term. It refers to self- knowledge through self- tracking (Quantified Self Institute). Due to technology innovations, many aspects of our lives can now be tracked, like sleep and heart rate. The quantified self creates a data double- you, but in data and numbers form. There are both positives and negatives to the quantified self. Positively, the quantified self allows for better health data. However, there are also many negatives. In Kathrin Rogella’s We Never Sleep the quantified self was created and the physical self faded away. The quantified self can take away joys in life. Additionally, the quantified self can allow for major governmental control, as seen in Juli Zeh’s The Method. The quantified self dehumanizes us. It is important to find value in the data, and not just let it take over our lives. 

I utilized the Garmin Connect app to monitor my heart rate, activities, steps (including  stairs), and activities such as recorded runs and walks. This data is useful to me as I am a runner and I like to look at my statistics to find ways to improve. The self observation also allowed me to think about privacy and security in relation to the app. I wanted to find out how much data would be available to others. It was also interesting to track my heart rate. It gave me insights to when I was stressed and when I was calm. Data like I collected allows me to have a better sense of self and change my habits. For example, if I notice I usually get stressed and my heart rate raises at a certain time, I can perform meditation or another stress relieving activity during that time period. Another aspect I get from my heart rate relates to my training. When my heart rate is over 180bpm, I know that I am pushing myself very hard. If it gets to near 200, I know I need to slow down or take a break. Personal data can be useful for many things in life. 

The Garmin Connect app allows for a great creation of the quantified self. It is great for measuring values such as heart rate and sleep. It can even monitor your sleep cycles and analyze them for you. The app is great for connecting with other Garmin users. Your personal data is somewhat protected. It will disguise your activities by placing them in the broader category of county. However, it is still possible to discover one’s location. Another benefit of the app is the user privacy settings. One’s profile, activities and badges have the option to be visible to everyone, only friends, only friends and groups, or only oneself. A worry is the default setting is set to everyone. 

My data is shared only with my friends on the app and Garmin itself. One concern I have is that my data may have been compromised when Garmin was hacked in July. The benefits of the app are that it allows me to connect with other users. I like to compete through the app with my uncle, who lives in another country. Another benefit is the choice in privacy settings. I also enjoy being able to monitor my daily progress such as steps and set step goals. The sleep feature is very useful for determining if I am well rested. Some drawbacks of the app are the minimal users of it. Another disadvantage is the outdated software. The app is very slow and the formatting is outdated. It could do with a major update as it has been the same for five years. Overall, I feel like my data is as secure as it can be for being on the internet. 

In The Method, the citizens in the society all have a tracker. The main character, Mia has a chip “in the same place as everyone else’s, in the middle of the bicep” (Zeh 58). In a way, society has progressed to this today. Between smartwatches and smartphones, we are all being monitored constantly. In the news, you hear people worried about the COVID- 19 vaccine. They believe there will be “a chip to track people” (Tregde). It is strange people have not recognized we are already being constantly monitored. A great thing about this class is how it has drawn my attention to this. Additionally, the class has given me ways to reduce the surveillance on myself. I think those that are worried about the vaccine need to do more research into their devices and apps to realize they are already constantly tracked. The chip is self- implanted. The chip for the vaccines is not for government use and is located on the outside of the syringe. This way, “healthcare workers will have the option to tag it with their phone. That will allow them to upload a date, time and GPS location of each vaccination in real-time” (Tregde). The common theme is surveillance, whether it’s of you or a vaccine. 

In our group, we discussed the different apps we used to collect data. Some of us used sleep apps, and some of us used the Apple Health app. The Health app and the Garmin Connect app are very similar. They both get the best data from having a compatible watch. One thing that stuck out to me in our conversations was how surprised we all were with how in depth statistics were measured. Ella talked about how her Health app tracked her speed when climbing stairs. It can be concerning how much data is being constantly collected. Other statistics like phone/ screen time usage allowed us to see how much of our life we are on devices. However, it is not all encompassing as laptop and TV time don’t get recorded. A benefit to using the watches is for us to record activities. I think that it helps me to stay more active, and I feel like people in my group would also agree. 

Works Cited

Quantified Self Institute. “What is Quantified Self?” Quantified Self Institute, http://qsinstitute.com/about/what-is-quantified-self/. Accessed 2 December 2020.

Tregde, David. “Verify: COVID-19 vaccine syringes to have trackers on the outside, not in vaccine.” WUSA9, 16 July 2020, VERIFY: COVID-19 vaccine syringes to have trackers on the outside, not in vaccine. Accessed 7 December 2020.

Zeh, Juli. The Method. Harvill Secker, 2012.

Final Surveillance Project: The Quantified Self

Data Diary

  • Wednesday, November 25:
    • I went into bed at 1:39 AM and was in bed for 5 hours and 42 minutes. I fell asleep for 5 hours and 31 minutes. I had 5 disturbances while I was asleep, but my sleep efficiency was 97%. I woke up at 7:21 AM and my respiratory rate was 18.8. I was a little tired, I definitely could have slept more.
  • Thursday, November 26:
    • I was in bed for 7 hours and 16 minutes and I went to bed at 2:26 in the morning and fell asleep at 2:39. I had 12 disturbances throughout the night and woke up at 9:55, having 6 hours and 44 minutes of sleep with a respiratory rate of 18.6. I slept pretty well besides the disturbances.
  • Friday, November 27:
    • I slept from 5:53 AM to 12:30 with a total of 6 hours and 28 minutes of sleep, but I was in bed for 6 hours and 28 minutes.I had 7 disturbances. My respiratory rate was 19.3. My performance throughout the day definitely suffered from my lack of sleep during the night.
  • Saturday, November 28:
    • I was in bed for 8 hours and 5 minutes and I fell asleep at 3:45 in the morning. I slept for 7 hours and 21 minutes until I woke up at 11:51 AM. I had heightened physical and mental energy from my 7 hours and 21 minutes of sleep. My overall performance from the day improved my extended sleep.
  • Sunday, November 29:
    • I was in bed for 6 hours and 44 minutes. I slept for 6 hours and 5 minutes from 2:54 in the morning to 9:39 in the morning. I had 6 disturbances throughout the night and my sleep efficiency was at 90%. My respiratory rate was at 19.2. I felt like I slept pretty well tonight.
  • Monday, November 30:
    • Although I was in bed for 8 hours, I was awake for about 40 minutes before I fell asleep at 3:02 AM. I woke up at 11:08 AM, for a total of 7 hours and 19 minutes of sleep. I got 75% of the sleep that I need with 91% efficiency but I had 7 disturbances. This was the best night of sleep I got.
  • Tuesday, December 1:
    • I was in bed for 3 hours and 59 minutes and asleep for 3 hours and 1 minute. I went to sleep at 3:01 AM and woke up at 7:03 AM. I had 5 disturbances, my sleep efficiency was 76% and my respiratory rate was 18.9. Getting only 3 hours of sleep increased my injury for the following day.

Reflection

To quantify, by definition means, “to determine, express, or measure the quantity of,” and self, by definition means, “an individual’s typical character or behavior.” A quantified self is self-knowledge through self-tracking. We are all being surveilled, whether it be by walking past a street camera, or using a credit card at a store, or tracking yourself while sleeping. Despite the fact that it may be scary or just weird to know that we are constantly being surveilled and tracked, it is not always bad. We need this surveillance to know the truth. To know what is actually happening in our lives and how it is affecting us. We rely on this information as a society to live and function the best way we can. To prove this, I used a tracking device called WHOOP, to track my sleeping patterns and how it affected my everyday life.

WHOOP tracks your physical activity, sleeping habits, blood pressure, breathing rate, heart rate, digestion, and more. All my information from the watch was immediately transferred to an app on my phone where I can check all my statistics. The watch is nice because it does not only track how long you sleep for or when you were in the deepest part of your sleep, it uses all your vitals during your sleep to compare how it affected you the next day. It also shows how what you did during the day affects your sleep. With this information I am able to determine exactly why I was not at peak physical ability during the day and what to do to make sure I am the next day. For example, on Friday, November 27, I did not sleep enough and the app told me, “You only got 5:53 of the 9:59 you needed. Performance suffered as a result,” and then proceeded to tell me all about my vitals from when I was sleeping. The next night I slept more and so my performance improved. I need this to improve on my daily life and to make sure my body is staying healthy.

Some sleep tracking apps that I have used in the past only require you to put your phone close to you while sleeping and from there, it documents your sleep. The WHOOP watch is different because it is not close to you, it is on you. It is the closest you can get to a tracking device, without implanting some sort of chip. “The WHOOP Strap 3.0 collects physiological data 24/7 to provide the most accurate and granular understanding of your body.” Although, in Juli Zeh’s, The Method, citizens do have to have a chip implanted in their arm to be tracked and to optimize the citizens’ health and daily life. The citizens are constantly being tracked, every second of every day of their life. Why were the citizens in The Method constantly being tracked? The same reason that we track ourselves, to optimize our health and ultimately, our lives. Juli Zeh agrees that, “Health is a state of complete physical, spiritual and social well being – and not the mere absence of disease,”(Zeh 1). It is scary to think of a world where we are forced to give our health information by a chip in our arm, but really it is necessary to track these aspects of our life. “Science tells us that you don’t get stronger in the gym (that’s what breaks you down), you actually get stronger during rest. Sleep can be the forgotten third of your life. It’s the period to repair, regenerate and prime your mind and body for peak performance. WHOOP measures not only how long you sleep, but the time spent in each stage to better understand sleep quality. The WHOOP Sleep Coach tells you exactly how much sleep you need to reach your desired performance level the next day.” Maybe it should not be a chip in our arm, but with an app like WHOOP or any tracking app, it is important to better our health and lives. 

As a result of WHOOP not just being an app on the app store, and it being a watch, you do have to pay for it. Though, the app comes free with the purchase of the watch. Being that the app records so much, there are some limitations, like the cardiovascular load. WHOOP announced that, “WHOOP Strain, reported on a scale from zero to 21, measures the total cardiovascular load experienced over a specified period of time – such as a workout or day – normalized such that a 21.0 represents the maximal cardiovascular load that could be attained in a day.” So really, the max for the cardiovascular load is the healthy amount you should be using a day. There are some more memberships you can sign up for different accesses to information, but the sleeping tracking portion is free.

In Kathrin Roeggla’s, We Never Sleep, citizens are in a constant state of pressure to work a twenty-four hour work cycle. Taking a break or breather is very much looked down upon, it is actually credited when one goes days or weeks without sleep. The value of these people’s whole lives are changed because of why they are being tracked. So in We Never Sleep, the people are praised for their lack of sleep and recognized as a bad worker when they do sleep; their constant tracking affects everything they do. “She wanted to stay in touch with herself, in fact, immediately… she had no regrets, she wasn’t sorry she wasn’t there anymore,”(Roeggla 8).I think that this book brings out some unfortunate situations in the world that we live in. There are some careers that carry so much work and it is expected that the employees never stop doing it, because when they do, they fall behind and someone else can take their position. In that case, I think that the book brings out an exaggerated mental and physical problem in the workplace. Nevertheless, We Never Sleep, in a darker way, shows how important it is to track sleep and help. Sleep is so necessary and tracking how we sleep is just as crucial. 

Not all students in my group tracked their sleep, but the ones that did had a very similar approach. We agreed that tracking sleep is so important for everyday lives and health. Other students in the group were still in agreement that a lot of data was tracked and that it is actually pretty important to know what is being tracked. 

As a society and as a person, we rely on our sleep information to live the best life we can and to stay as healthy as we can. The quantified self has proven through many different ways of tracking, that we are living in a world of surveillance. Technology has allowed us to prevail and better ourselves as a society. If everybody embraced the technological world we are living in and used these resources to help ourselves and everyone else, society as a whole could have the potential to become great. Looking at We Never Sleep and The Method, we are able to compare them to the world that we live in and see just how important and useful self tracking our sleep is in our world today. We have the chance to better ourselves in every way, why not take it? 

Works Cited:

Labs, DI. “The World’s Most Powerful Fitness Membership.” WHOOP, 2 Dec. 2020, www.whoop.com/?gclid=CjwKCAiAwrf-BRA9EiwAUWwKXky5drRFVvkuQ0iHRNKZ6-MVjKk_0c5JfpO2wMPBjsipe_4E1OAY_xoCfKQQAvD_BwE. 

“Self.” Merriam-Webster, Merriam-Webster, www.merriam-webster.com/dictionary/quantified. 

“Quantified.” Merriam-Webster, Merriam-Webster, www.merriam-webster.com/dictionary/quantified. 

Röggla, Kathrin, et al. We Never Sleep. Ariadne Press, 2009. 

 Zeh, Juli, and Sally-Ann Spencer. The Method. Vintage Books, 2014.

 

The Quantified Self

Surveillance Project Diary :

11 / 30 – Monday :
Today I burned 505 calories. I exercised for 18 minutes by walking my dog luna and walked 9,372 steps. I climbed nine flights of stairs by going upstairs to my bedroom. I found a new element that my apple watch tracks. My apple watch tracks how fast I go up the stairs. Today I walked up the stairs at a range of 1.3-1.9 ft /s. I stood up for at least one minute for 15 hours. I also walked approximately 4.3 miles. My heart rate range was from 72-84 BPM. The sound levels around me ranged from 36 – 81 dB. Today was a pretty active day for me, although I could not work out as much as I would like. Beginning this project, I cannot help but weigh the positives and negatives of allowing others or the government to have access to my health data. Like Mia in Juli Zeh’s The Method, I find myself more reluctant to allow the government to use my health data for “research purposes” because I am not optimistic that that is really what it is being used for.

12 / 1 – Tuesday :
Today I found many new features on my apple watch: resting calories, the time I stood, resting heart rate, step length, and walking speed. Many of these features that I discovered today reminded me of new surveillance and how, in our modern age, we can have items such as apple watches that work with our senses and cognition. I burned 461 calories and burned 1,422 resting calories. I exercised for 21 minutes and walked approximately 4.1 miles. I also completed 8,954 steps. I stood up at least one minute for 15 hours and stood for a total of 125 minutes. I had three classes, which is why I did not stand up much throughout the day. My environmental sound levels ranged from 32 – 102 dB. My heart rate range was from 62 – 149 BPM with a peak of 149 at 4-5 pm, probably because my mom told me dinner was ready, and I got excited. My resting heart rate was 80 BPM, and my walking heart rate was 119 BPM. My step length was 26.4 inches, which surprised me a lot since I am 5’2. My walking speed was 3.1 mph and how fast I walked up the stairs was 1.6 ft /s. Today I was less active than yesterday, but considering I have three classes on Tuesdays, I feel as though I was productive

12/2 – Wednesday:
Today my apple watch tracked that I burned a total of 401 calories. It showed that I exercised for 16 minutes and stood for one minute in 14 hours. I took a total of 7,159 steps and walked for around 3.2 miles. In total, I stood for 120 minutes along with climbing 12 floors. I had 1,426 resting calories, my average heart rate at about 111 beats per minute. My environmentally sound levels were similar to the day before, being at 32-93 dB. My resting heart rate averaged 71 BPM. With my step length being 18.9-29.1 inches, my daily speed ranged between 1.9-3.7 mph. Today I checked my settings to see where all of my data was going. I was happy to find out that I do not allow my data off my apple watch to be shared with other apps or used for research purposes. I feel as though only seeing myself through my Apple watch’s eyes that I often caught myself appearing as just a number in a system, which made me feel a bit odd since my apple watch is supposed to be personalized to me.

12/3 – Thursday :
Today I burned 401 calories and burned a total of 1,477 resting calories. I exercised for 16 minutes, which is lower than usual. I traveled 3.2 miles and completed a total of 7,197 steps. I stood up for at least one minute for 15 hours and stood for 90 minutes. I was not happy at the amount of time I was sitting today, but I guess that’s what comes with all of my online classes. I climbed 14 flights of stairs. Today I noted that my watch calculated both my speed going up and down the stairs. My rate down the stairs ranged from 1.1 – 1.6 ft/s while my pace up the stairs was 1.6 ft /s. My environmental sound levels ranged from 32 – 95 dB. My heart rate went from 54 – 144 BPM with a resting heart rate of 68 BPM. My walking heart rate was 68 BPM, considering I barely walked today, and my walking speed was very slow at 1.6 – 3.2 mph. My step length was 18.5 – 28. 7 inches. Today was not a very active day, but it probably means I was super studious. Throughout the day, I was reminded of how surveillance is an exercise of power and how when we are surveilling ourselves, we often take away the control that the government has over us as Hasan M. Elahi did his “Tracking Transience” throughout his day through pictures.

12/4 – Friday :
Today my apple watch tracked that I burned 456 calories and had a total of 1,490 resting calories. I exercised for 30 minutes and was pretty active, and traveled 3.9 miles. I took 8,769 steps and stood up one minute in 14 hours, and stood for 113 minutes. My heart rate ranged from 61 – 151 BPM and rested at approximately 79 BPM. My walking heart rate was 113 BPM. Today I climbed 19 flights of stairs, and my speed up the stairs was 0.92 – 1.6 ft /s, which was lower than usual, and my pace down the stairs was 1.2 ft /s. My environmental sound levels stayed approximately the same as it has been for the past couple of days at 32 – 93 dB. I found another new feature on my watch that calculated how far I walked in six minutes, and it said in six minutes I walked 500m. My walking speed averaged 1.4 – 3.6 mph, and my step length was approximately 16.9 – 31.9 inches, which was larger than usual. Overall, it appeared that I had a pretty active day.

12/5 – Saturday :
For Saturday, I burned a total of 438 calories while exercising for 22 minutes. I took a total of 7,201 steps, totally out to be around 3.3 miles. I had 1,498 resting calories with my resting heart rate at 71 beats per minute. I stood for a total of 102 minutes and climbed ten flights of stairs with my stair speed up being between .85-1.3 feet per second and my stair speed down being 1.9 feet per second. My stair speed up was a little slower than usual. My environmental sound levels were 32-107 dB, and my heart rate ranged between 66-147 beats per minute. My walking speed ranged between 2.1- 4.2 mph, being the fact that I went out with friends and walked around town. My step length for the day was considerably longer than usual, between 19.7-35.8 inches, slightly raising my average walking heart rate to 118 beats per minute. Overall, I had an eventful day but am super excited to head into the last week of school and be done.

12/6 – Sunday :
Today was a great day because I am finally done recording myself, I’m just kidding. It was a great day because I went Christmas shopping for my mom. I burned a total of 426 calories and burned a total of 1,376 resting calories. I walked 4 miles and completed 16 minutes of exercise. I met 8,917 steps, and my step length was 26 inches. I stood up at least one minute for 13 hours but stood up for a total of 129 minutes. I climbed nine floors, and my speed up the stairs was 1.4 ft/s, and my pace down the stairs was 1.3 ft/s. My heart rate was 96 BPM when I collected this data and varied 24 ms. My resting heart rate was 76 BPM, and my walking heart rate was 120 BPM. My walking speed was 2.4 mph. My environmental sound levels were 38 – 110 dB, with a peak of 110 at 9-10 pm, possibly due to my dog barking. Today I found a new feature called walking asymmetry. Walking asymmetry is used to see how well you’re walking by taking both the left and right sides of your body. My walking asymmetry was 3.4 %, and I believe that healthy walking asymmetry is 5 %, so I need to do better walking evenly. After collecting data for a week on myself, I have realized that if I do not complete specific goals such as exercising each day, I often feel inadequate and let that get into my head. Users need to realize that your data does not define you as a person and your identity.

 

Reflection :
In recent years, Apple came out with its first Apple Watch. The Apple Watch can track your exercise, heart rate, environmental sound levels, and much more. Like myself, many people were fascinated by the Apple Watch and its capabilities and purchased the watch. For a week, I tracked my activity through my Apple Watch to explore my data that the watch was tracking. Throughout the week, I found many new features on my watch that I didn’t know existed and played with my settings to see who was accessing the data from my watch.

There are many elements of our lives that we monitor. From our heart rate, running pace, sleep patterns, or step count, we are continually surveillancing ourselves. According to Live Science, the quantified self refers to the “increasing use of technology to collect data about oneself” (Rettner). Through this project, I understood private versus public information and the importance of being aware of who is accessing data that you plan to keep secret. I was also able to know how through surveillancing yourself, you often take away the power that the government has over you as Hasan M. Elahi did in his “Tracking Transcience” through always documenting elements of his life like the food he ate, flights he was on, and much more. Through this, Elahi was able to take power away from the government and back to himself. In many ways, throughout the week, I felt that surveillancing myself allowed me to feel like I was in charge of my data. As I explored my Apple Watch, I was made aware of many aspects of my watch that would be considered new surveillance and how these new technologies could be beneficial to us and harmful at the same time.

On my Apple Watch, I mainly measured my activity throughout the day, including calories burned, how long I stood up, how many steps I took, my heart rate, and much more. I chose to measure this because I was interested to see how my activity changed over the week and to see what factors in my life played into my mobility and movement. For example, on Tuesdays and Thursdays, I would often note that I had significantly fewer minutes that I stood. I concluded that this was more than likely because I have three classes on both Tuesdays and Thursdays. Therefore I am less active on those days of the week.
My observation of myself was to understand my Apple Watch and understand where my data is going. Before beginning this experiment, I did not know many of the features of my Apple watch. For example, I was unaware of the element that measures my Environmental Sound Levels and how that, in a way, means that my Apple Watch is listening to everything that is going on around me. On the second day of my experiment, I checked my settings to see where my data collected from my watch was going. I was relieved to find out that my settings were that I did not allow any other apps to access my data, and I did not allow for my data to be used for research purposes.

The knowledge that I planned to gain throughout the experiment was seeing what patterns my activity took over the week and what similarities I could draw from day to day. I also planned to gain knowledge from Apple by seeing how accurate I felt the data collected. In some instances, I often would move my arm that my watch was on, and it would count that movement as me exercising when I was not. I will go into more detail about this later.

The data my watch collected was generally valuable to me. In some instances, I felt as though some data was more useful than others. For example, my step count was less helpful because it is merely just a number, in my opinion. The data that was more valuable to me featured such as my heart rate and my data patterns over a period of time because that data is much more personal to me and, in my opinion, is my private data. I know that I found myself feeling like a statistic rather than a real human being in many cases, but I was also aware of the importance of protecting what I felt was my private data.
Overall, I was pretty satisfied with the data that my Apple Watch collected. I enjoyed exploring all of the different features that the watch had to offer and was amazed at just how advanced the technology was from a small item. As I stated above, my data was not shared with any other apps or used for research purposes, but I imagine that Apple may use the data without telling us, which would not surprise me. Throughout the week, I contemplated the benefits and the negatives of using the Apple Watch. Many of the services I found were that you could track an array of elements of your life and set daily goals for yourself. For example, my everyday goal is to burn 400 calories, and that goal motivates me to be active throughout my day. In many instances, I was reminded of a specific quote from Juli Zeh’s The Method. Zeh states, “The Method was developed so that every individual can enjoy maximum longevity and minimal biological dysfunction – or put simply, a happy and healthy life, a life free from suffering and pain” (29). Although there are many benefits to having the data readily available to us, we run the risk of becoming addicted to the data and getting too wrapped up in our data, and allowing it to affect our mental health. I often find myself getting upset when I do not exercise enough and find that affecting my mental health, and that is something that needs to be considered when collecting all of this data about ourselves.

Although I used my Apple Watch, other group members utilized apps that tracked their sleep or tracked their speed while driving. I found that interesting because we all chose different apps that displayed that there is so much potential data that could be collected under the quantified self. In general, I believe that most of the group was shocked at the amount of possible data our electronic devices could collect without us even being aware of it. Overall, through this project, I gained a better understanding of private versus public data, the mental health risk of this data, and just the amount of data collected on us. Through this experiment, I felt as though I realized just how powerful surveillance is and how often those who surveillance others often possess power over whom they are surveilling. The aspect of control regarding surveillance is essential and is something that we need to look out for as our world continues to progress and increase its technology.

Works Cited
Elahi, Hasan M. Tracking Transience v2.2, elahi.gmu.edu/track/.
Rettner, Rachael. What Is the Quantified Self? 26 Aug. 2013,
www.livescience.com/39185-quantified-self-movement.html.
Zeh, Juli, and Sally-Ann Spencer. The Method. Vintage Books, 2014.

Life 360

*Note: this data is from a full week. The first photo shows overall data and the next three show individual data for each day

 

Data Diary:

Monday: On Monday November 30, my friends and I spent lots of time on our phones collectively. Combined, we spent over 10 hours using our phones. While it doesn’t show a specific value after 10 for each day, the weekly hour number was 248. If you divide this by 7 days and then by 9 people we each averaged around 4 hours a day on phones. Next, we only had 2 hard breakings but no rapid accelerations for that day, which is pretty low!

Tuesday: On Tuesday December 1, we again each spent around 4 hours plus on our cell phones. After looking at my screen time, it is clear that I actually went above that time period for most days so taking the average of my friends was not as accurate. We also had 4 (which is the maximum for the week) hard breakings and 2 rapid accelerations.

Wednesday: On Wednesday December 2, we all averaged around 4 hours on our phones. After looking at my screen time, it was clear that I actually averaged closer to 8 hours! We also hit the maximum amount of hard breaking (4) and had a maximum of 3 rapid accelerations.

Thursday: On Thursday December 3, the phone average was the same but I spent 7.5 hours on my phone that day. We had 3 hard breakings and only 1 rapid acceleration.

Friday: On Friday December 4, the phone average was again 4 hours but I spent 7.25 hours on my phone. We had 1 hard breaking and no accelerations. This was the day that most of our group started to quarantine. My friend Riley got COVID so all of my friends began the process of quarantining and getting tested.

Saturday: On Saturday December 5, the phone average was again 4 hours but I spent 5 hours on my phone. We had no hard breakings or rapid accelerations; this is probably because no one was driving since all of my friends were quarantining.

Sunday: On Sunday December 6, the phone average was the same but I spent 7 hours on my phone. After talking to my friends, I learned that each of them all spent above 4 hours on their phones from Friday to Sunday, most likely due to isolation and boredom. We also had no hard breakings or rapid accelerations because no one left their house.

 

Reflection

My data diary consists of the data collected from Life 360 within the past week. The term quantified self is defined as “the act of using personal data to improve one’s quality of life” (Investopedia). In today’s technology driven world, our data is tracked in about everything we do whether we know it or not. Among studying and listening to the first episode of “The Privacy Paradox”, it was apparent that our data is extremely useful for large corporations. Many think that their collected data is being given to the government in order to track us and spy on us, when in reality it is actually being sold to companies for a lot of money. Companies use our personal data to improve their products and learn how to advertise them better. For example, our phones use their microphone to listen to us talking in our free time. They will then use that data to formulate personalized ads for products we may have talked about. While this may be nice for easy access, it is an invasion of privacy and should not be permitted. 

I would like to explain my data a little more before I analyze its purpose and dangers. My friends and I have an online group on the app Life 360. Life 360 is an app created for parents that allows them to track their child through their cell phone. The app allows parents to view location at all times, phone battery, driving speed, and much more. In my data shown, I collected the driving reports of my friends for the past week. The first photo shows the average stats for the week, including total miles driven, top speed of the week, and how many drives we collectively had. Each photo after this shows the detail for each day  for the past 7 days in each category. For example, you can see that there were 4 “hard brakes” while driving on Tuesday. I chose to measure the data from this app because I feel that it is the most intrusive. I have the app for fun with my friends so we can see where each of us are but I wanted to take a closer look at it. While it is a nice safety feature for teenage girls living in a major city on their own, I often wonder if it is worth it to have. The means by which it tracks you is quite creepy to me. The goal of my self observation is to determine whether Life 360 is a safe app and also to figure out where our data goes. The data on the app is very valuable to me as it shows where I live, how I drive and where my friends live as well. 

Next, I would like to analyze the actual app and try to figure out where my data goes. After reading reviews on the app, it is safe to say that it is not favorable by any means. Many people have reported that the app actually shows them in a different place than they actually are. One of the reviews was a man saying that the app is responsible for his divorce; it said he was somewhere he was not and his wife assumed he was cheating. I find this review really funny but in reality, it can actually complicate and harm families. I also found something that is making me delete the entire app for good; Life 360 actually sells your data to companies. Not only are your locations and statistics sold, but your driving record is sold to insurance companies. Many people have deleted the app because their insurance rate has gone up because of the app. The app tracks your top speed, how many fast accelerations and hard brakes you have, and also detects crashes. People are getting charged for their driving habits without their knowledge because of Life 360. What started out as a fun app for me and my friends turned into something quite harmful to me which I will be deleting. 

This app reminds me of the telescreens in George Orwell’s “1984”. The telescreens that track the citizens of Oceania follow their every move without their knowledge; it even tracks their thoughts. Orwell states “The telescreen received and transmitted simultaneously. Any sound that Winston made, above the level of a very low whisper, would be picked up by it; moreover, so long as he remained within the field of vision which the metal plaque commanded, he could be seen as well as heard. There was of course no way of knowing whether you were being watched at any given moment” (Orwell 66). Like the telescreens, Life 360 has no way of shutting off unless you delete it. Like I said, my friends and I have the app for fun but the most common use of the app is for parents to track their children, in which the kids have no way of turning it off without their parents knowledge. While this app is a great safety feature, it is completely unfair and an invasion of personal data and I think it should be banned from selling information to insurance companies. 

Lastly, I would like to address my group members data recorded. I remember that Ella was going to use her Apple Watch to track her physical activity over the last week. After looking into the Apple Watch, it is clear that Apple promises that customer health data won’t be sold out to third party companies. I think that the watch is a great way of staying fit and will help a lot of people track their fitness and weight loss. For me, using my Fitbit is really great because it motivates me to complete my step goal for the day and does no harm. Apps and devices like these are really useful for people and I don’t think there’s a harm in using them for your own personal gain.

 

Works Cited

“FYI, Life360 Sells Your Location Information, Driving Habits, and Registration d…: Hacker News.” FYI, Life360 Sells Your Location Information, Driving Habits, and Registration d… | Hacker News, news.ycombinator.com/item?id=20890649.

“Life360 Reviews – 2.6 Stars.” Sitejabber, www.sitejabber.com/reviews/life360.com.

Orwell, George, et al. 1984. Grasset, 2020.

Peters, Katelyn. “Quantified Self.” Investopedia, Investopedia, 26 Sept. 2020, www.investopedia.com/terms/q/quantified-self.asp.

 

Surveillance Project

Digital Diary:

  • Thursday, November 19, 2020
    • I was in bed for a total of 9 hours 8 minutes and was technically only asleep for 7 hours 31 minutes. Woke up around 8:30 which is earlier than usual but I still feel fully rested. By having the phone so close the app was able to pick up on my movement by sound and calculate exactly what I was doing. It tells me I fell asleep at 11:33 pm and that I did not snore. It even comes with a graph to show me when I was in a deep sleep, and from looking at the graph I’m able to confidently say that I slept the deepest between 5 and 7 in the morning.
  • Friday, November 20, 2020
    • I was asleep for 8 hours 51 minutes. Went to bed at 12:30 and fell asleep 30 minutes after getting into bed. I was in my deepest sleep between the hours of 3 and 4. My quality of sleep was 100%. I woke up at 10:35. I felt as though I had slept pretty heavily and I was well-rested when I awoke.
  • Saturday, November 21, 2020
    • I was asleep for 7 hours 38 minutes. Went to bed at 2:26 and fell asleep 10 minutes after getting into bed. My deepest sleep was recorded between the hours of 3 and 4, again. My quality of sleep was 98%. I woke up at 11:32. Like the previous night, I slept pretty well and I did not wake up tired.
  • Sunday, November 22, 2020
    • I was asleep for 5 hours 2 minutes. I went to bed at 3:48 and fell asleep 6 minutes after that. My sleep quality was 61%. I woke up at 9:03. Even without the tracking of the quality of my sleep, I could tell you I did not sleep so well, probably because I went to bed close to 4 in the morning.
  • Monday, November 23, 2020
    • I was asleep for 7 hours 15 minutes. I went to bed at 1:22 and fell asleep 25 minutes after that. My sleep quality was at 71%. I woke up at 9:28. I got a better night’s rest, I feel like I didn’t get into a deep sleep like the first two nights.
  • Thursday, November 26, 2020
    • I was asleep for 8 hours 30 minutes. I went to bed at 11:49 and fell asleep after 11 minutes. My sleep quality was 77%. I woke up at 9:18. Woke up around 1 in the morning but was quickly able to fall back asleep but still not the best sleep of this week.
  • Sunday, November 29, 2020
    • I was asleep for 7 hours 31 minutes. I went to bed at 11:18 and fell asleep 10 minutes after that. My sleep quality was 93%. I woke up at 8:05.

Surveillance Project

Imagining a world where your worth is based on a singular parameter whether that be by how smart or strong you are is terrifying. We preach that judging someone based on their appearance is wrong, the dystopic pieces of literature we see nowadays evolve around the mistreatment of a certain social group. We act as if we aren’t in a dystopic world ourselves but we are. What all these dystopic worlds have in common is that self-tracking is apparent and necessary. Movies from the Divergent and Hunger Games franchise depend on one’s quantified self meaning that whatever can be measured about ourselves, strength or intelligence, is taken more into account than anything else. To demonstrate this theory I will self-surveil myself by tracking my state of sleep through SleepCycle. 

You know that self-tracking is real when you have apps that can surveil you in your sleep. Unlike the fitness apps that require you to physically move your body the SleepCycle app just requires that you have your phone close by to listen to your breathing and movement. You’re not logging any information into this app, which is the main reason why I chose this app but also because when you’re asleep you’re in your most vulnerable state yet the data that’s collected ranges from whether or not you snore to what time you were in your deepest sleep. Often surveillance is easily noticeable within society either by street cameras or just recognizing that when you’re googling something there’s a chance someone is storing your search somewhere.

However, when you’re surveilling one’s sleep the parameters shift because the subject is asleep, and the only way to analyze someone in that state is by sound analysis. The data collected over the seven days go towards SleepCycles’ study on “finding your perfect wake up window, we believe you’ll be part of the change, for the benefit of better health” (SleepCycle). The benefits of this app are that you get a detailed analysis of your sleep for free. Unless you think that your sleep schedule being used for a worldwide study is bad the only limit is that to access an even more detailed version of your night you have to pay for a premium version. However, what this app does reveal is that even when you turn your phone off it doesn’t mean it stops collecting data.

Unlike Katherine Roeggla’s We Never Sleep where going days without sleep is rewarded I chose an app that revolves around one’s sleep. By monitoring my sleep I was able to better understand the parameters in which surveillance works. Eventually, by three days the app was able to calculate the quality of sleep for each night due to the information that was collected the previous days. By self-tracking myself through an app it became very clear what little I had to do to be surveilled. After waking up I would check the app and it would always feel as if it wasn’t me tracking myself because I was unconscious and unaware of what I was doing. In Roeggla’s We Never Sleep the senior associate claims “it wasn’t really him doing the job. It was more that he was playing a role” (Roeggla, 11) and to an extent, I find that very relatable when I was self-tracking. Despite being unconscious, knowing that I’m self-tracking has to factor into this “experiment”. It makes me question whether or not my sleeping pattern would be different if I had not known that an app was tracking my sleep. Being aware of this could easily not have any toll on my sleep, however, in most human experiments it’s preferred when the subject knows nothing of the actual experiment being performed. In the world of surveillance, I feel as though the information would’ve been more interesting to look at if I were unaware of the tracking. Creepy I know, to think of someone tracking you in your sleep without your knowledge but I feel like this happens more often than we realize. 

Sleep plays a huge role in one’s health. In Juli Zeh’s The Method the health of every individual is their constant priority. In this dystopian novel, the citizens are to provide their form of government with their sleep patterns along with other health records, and if an individual doesn’t submit the medical data they are held accountable for breaking a law. The protagonist, Mia, says “Since life…is meaningless and yet you have to keep going, I sometimes feel like making sculptures out of copper pipes” (Zeh, 18). I believe this is a metaphor portraying the world she lives in and how she views the system and laws by which she currently has to abide by. For example, she says she’d call these sculptures “temporary structures” maybe referring to how easily collapsible the system in place is. She even goes as far as to say that “I’d like to make something that will last” (Zeh, 18) which could easily resemble the world we live in now. We have made surveillance a permanent fixture in our lives that can easily be manipulated just like in Zeh’s novel. One’s health is considered a private matter, however, in this novel health is manipulated with the belief it could better the world they live in just as surveillance is in our world. 

The group discoveries found we’re all similar. Although no one else self-tracked their sleep, everyone was all surprised on how much data was collected from their apps. Many said they often forgot about the self-tracking until it was time to summarise the data. That point fits perfectly into my experiment because I was asleep and unaware of what was being collected almost like forgetting I was self-tracking. 

The quantified self has embedded itself within our culture forcing us to view things differently. What we prioritize, value, and become reliant on has changed drastically over the years. Through authors like Katherine Roeggla and Juli Zeh, we have come to understand the world we are becoming. By reading pieces of literature like We Never Sleep and The Method readers can easily compare the novel’s plot to today’s society, for example, surveillance. It’s all around us, intended for our own security and safety and dependent on the citizen’s little knowledge of it. Just like in the app I used for my self-tracking experiment, SleepCycle requires the bare minimum from the user. Monitoring you during the part of the day when you’re least aware, solely dependent on a device close by to listen to your movement. The bare minimum has a way of taking advantage of what little knowledge we have on the world around us.

Work Cited

Zeh, Juli, and Sally-Ann Spencer. The Method. Vintage Books, 2014. 

Röggla, Kathrin, et al. We Never Sleep. Ariadne Press, 2009. 

SleepCycle App https://www.sleepcycle.com