Tag: data logs

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I started my day in the Student Center, as I worked there overnight Sunday. The study space has tap access so every time I used the bathroom or filled up my water bottle I would use my ID giving location data and information about the usage of the space.

I bought a plane ticket. This is notoriously a process that takes a lot of data using cookies. I also bought this ticket after monitoring a price tracker with alerts for the last two months and waiting for the price to drop. I bought the ticket after receiving an alert e-mail and following the link in the e-mail so there is data given to google about how successful this service is. I also used my credit card to buy the ticket.

P-set printing, using the Athena system and my MIT ID

Overleaf – Writing in LaTex on an online editor meant constant data transfer. I also continually used google for help with the project I was working on.
Google Photos – I take pictures of notes etc. Google Photos has a feature that allows you to search your own photos using tags that they have given it using AI/Machine Learning. I would search my photos for words like “blackboard” to filter to the photos I had taken in class. When you make these searches the algorithm improves by looking at what you click after the search is completed.

I went to Dunkin to buy a bagel – used a debit card

While working, I used my phone continually. I would check my phone, group.me, Instagram, text, Snapchat – on all these apps they collect data on how long I use the app which buttons I press what I like what I don’t like.

Walked back to my dorm where I use my MIT ID to gain access.

Youtube – I use youtube to watch “comedy bites” – clips from tv shows compiled into smaller chunks because I don’t have time. Youtube is collecting data on what videos I watch all the way through vs when I choose another. They collect data on how long I watch an advert before I click “Skip Add”. They also let you up/down vote on adds to collect data on what you do and don’t like. I don’t click these but even refusing to participate is data.

I then went to class – I use paper to take notes so no data there but I do check my phone during class so the previous discussion continues

I attending a 6.036 (Intro to Machine Learning) LA meeting. Used Google Docs to give feedback on homework. I then helped at office hours for 6.036. There is a queue system where people go online ask for help and then I click a button to say I am currently giving them help. This collects data on how many people I help and how long it takes me to help a student. I also use a google form to check in and tell the staff that I turned up for my shift. We also use an online code editor which collects information on usage

I reported my weekly worked hours on ATLAS so I can get paid.

Online CrossWord Solving with friends – timing how long it takes me to complete the crossword.

In addition, Google Maps creates a map of where I’ve walked however I chose to not include this here for safety.

Chatting with people

I have a very sick (not in the cool way) morning ritual. Every day literally starts with me snoozing the alarm and then checking my notifications for any messages which popped up during the night (people who come from places halfway across the earth will empathise with me)!

I use quite a few applications to chat with people. People back in India prefer using WhatsApp. Friends and classmates here in the US prefer Slack and Facebook messenger. Instagram messaging is mostly for sharing memes and funny videos (but it counts, right? Because the memes people share can say a lot about them :P). Emails (outlook and gmail) and LinkedIn is reserved for professional conversations. Also, does piazza count?

Moving around

The weather was amazing today and I decided to bike to school instead of taking the bus. I used Bluebikes twice today and it collects information about the start station, end station, start time, end time, etc.

I used my credit card a couple of times today, to buy a coffee and later a candy bar in a vending machine. So my credit card company probably knows exactly how much calories I gained in that delicious smoked butterscotch latte!

I also used the WiFi at MIT and later in the cafe. And my data is always on! I guess all of these people could track my location while I was connected to their network.

Getting Online

I listen to a lot of music. I was shocked when Spotify released the amount of music I had heard in 2019. It was around 60k minutes! Spotify is probably my most used application and it collects a lot of information on me!

I use Instagram and like every 20 something person I’m sorta addicted to it. I use Facebook too, but not as much as I used to use it 5 years ago. I spent a lot of time today on Stack Overflow searching for some python and R things that were hindering me from completing a few homework.

I also use Amazon Fresh, but today wasn’t groceries day! But I did use Amazon to search for a shiba inu plush and a giant Hershey bar!

Other breadcrumbs

I don’t use much Twitter, but today was a special day. Trump is visiting India and he made some hilarious pronunciations (or rather mispronunciations) of some Indian names during his rally. Indian Twitter is lit up with memes and videos and I spent a good half an hour laughing!

Chatting with People

The majority of my interpersonal communication takes place via gmail, Facebook messenger, and Slack. A couple of days ago I read that Facebook has started fully encrypting their messages, so I guess there is no way that could be used as a data set. In the evening I had a conversation with a friend that I’m sure was picked up by their Amazon Echo. I also intermittently messaged friends via Signal throughout the day, an app we use specifically because it does not retain any information on sent messages.

Moving Around Town

I started the day by tapping my van into the MIT commuter lot by Simmons. From there I tapped into the Z Center for a workout before heading into lab (which was definitely caught on security cameras). I didn’t leave the lab for seven or eight hours, but I filled my water bottle several times at one of those smart water fountains that tracks water usage. I also took pictures and videos of my work throughout the day which includes time and location metadata. In the evening I went to work in Darwin’s Coffeeshop, where I was recorded on CCTV and I made a credit card purchase. I also logged onto the Darwin’s WiFi.

Getting Online

The non-communication websites I visited today are Reddit, Instagram, YouTube, Google Drive, Dropbox, and the Solidworks Forums (all of which I have personal accounts with, allowing them to track what I view). I played some video games through the Steam App, watched some Netflix, and used the streaming services Spotify, Soundcloud, and Apple Podcasts. Can’t miss a single minute of NPR! I also logged onto the Data Storytelling Studio website 🙂

Other Breadcrumbs

I used Venmo to pay my rent this morning, filled out my absentee ballot (which is not yet online data but soon will be), and operated a 3D-printer that was connected to the internet. Finally, I signed off for a friend’s package with UPS so in a way I gave my data fingerprint (but I would argue that since I signed my friend’s name I did not really reveal anything about myself).

Chatting with People

On this day, I used Messenger and Snapchat to communicate with others. I mainly messaged about what I was doing that day, both with pictures on Snapchat to my friends or message updates to my girlfriend on what I was doing and when I would be back. My snaps could locate me at MacGregor, at Boda Borg, and the place I went to dinner at. If someone wanted to, they could easily trace what I did that day just through my messages and snaps.

Moving Around Town

I stayed in my dorm until around 2:30, during which the security cameras could have caught me leaving. I walked to the Kendall T station, in which I used my MIT ID to pay the fare. I rode to Downtown Crossing and transferred to the Orange Line, riding until Malden Center. I walked to Boda Borg, in which I used a signed electronic waiver, once again marking my location. Afterwards, I had dinner at a nearby Asian restaurant, in which I used my debit card. I then traced my steps back to MacGregor, once again using my MIT ID to pay the fare at Malden Center. My day ended with me tapping into MacGregor, once again signaling my location.

Getting Online

I browsed Facebook throughout the day for roughly twenty minutes. I scrolled through various posts and some comment sections, but never liked or reacted to anything. I also played a game on my phone, Hearthstone, for about an hour online with random people, but with no communication to them.

Other Things

My phone likely tracked my location, at least while I had it on briefly when looking for food places after Boda Borg. Who knows how many cameras I passed throughout the day who could have identified me if needed.

Chatting with People

I was in constant communication with people over WhatsApp and IMessage throughout the day, including sharing a playlist I made on Spotify with two people who then both used it to run – which I’m sure Spotify noticed. Around 2 I logged into the MyFitnessPal app to enter what I’d eaten in the day, and was prompted to allow location access, which I said yes to without thinking, and then immediately paused to wonder why a nutrition app needs my location – so I went back into my app settings and turned off its location access, but at that point it would’ve already located me at least once today. I also checked the weather app frequently, which tracks my location.

Moving Around Town

To start, I wear a Fitbit every day, so my walk to my friend’s home for breakfast, my run, and my errands were all tracked, along with my location and heart rate.

At 2:30 I went for a run, and using Strava to track the run which absolutely takes my location/ route and stats, and listened to a playlist on Spotify, which I always listen to when I run, and which I know Spotify stores the statistics on (my annual roundup of most listened to music on Spotify is always a carbon copy of my workout playlist). On the run, I would’ve been recorded on multiple cameras, as I ran by MIT’s campus and multiple banks and retail buildings.

Later in the day I walked to Whole Foods for a few ingredients for dinners for the week, and paid using my credit card, which allows Whole Foods to identify my and add my purchases to their profile on me.

Around 8pm I then realized that I needed quick oats for a cookie recipe, so I ran out to the convenience store on the corner, which has security cameras that recorded me, and where I paid for my purchases with my credit card.

Getting Online

I googled the results of the Nevada caucus in the morning, and then immediately followed that with a google about what the process of the Nevada caucus is, which other states have caucuses instead of primaries, and then what the schedule of the next few primaries/caucuses are.

I checked the Data Storytelling website midday, including logging into WordPress, to get a sense of how to write this blog post, and then logged into my Outlook email, which I’m sure Microsoft timestamped/recorded. I then logged into google calendar to add several events to my week based on emails I was checking.

While I was cooking dinner, I logged into my sister’s amazon prime account to watch a show, which would have logged what I watched and for how long, as well as possibly my location(?) – I’m fairly sure amazon must know it was me and not my sister. I then also looked up a recipe I was following on a blog, and then re-googled the Nevada caucus, and results were still being reported.

Other Things

I wear a Fitbit every day, so my walk to my friend’s home for breakfast, my run, and my errands were all tracked, along with my location and heart rate.