It all began thirteen years ago. What began thirteen years ago you may be asking yourself? It was a normal weekday evening as I finished my third grade homework assignment thinking about the episode of SpongeBob that I was going to watch when I was all done when my mother approached, she asked if I had ever used the Internet. I replied that I hadn’t and she insisted that I do so. She told about its endless possibilities and wealth of knowledge so readily available and I became intrigued. Unknowingly, this is where it all began. This is where a set of 1’s and 0’s gave the power to a machine to learn more about myself than any other human knows, which brings me to the purpose in writing this paper. Over the past few weeks I have analyzed some of the data that Google possesses about me over a period of 3 months from December 2015 through February 2016. This research has led me to the conclusion that, while incredibly advanced, it is impossible for a computer to truly understand the complexity and meaning of someone’s intentions, 
The time period where I have decided to analyze my Google data is a time where I was at a low point in my life and was looking for something to bring me out of it, so I turned to fitness. I didn’t have the slightest clue as to what was involved with fitness, so naturally I turned to the Internet. Over the next several months I searched a wide range of queries to help build my knowledge on fitness and weight lifting. In turn, I was giving Google knowledge about myself. Through this project, I have worked to develop 2 additional narratives that Google may have interpreted as being relevant to myself. 
	The unique thing about an algorithm making conclusions compared to humans is that an algorithm can only use the information that you provide it. It can’t stalk your social media accounts or ask your friends/family for details about some important life event that you didn’t want people to know about. So, how do these advanced algorithms make conclusions? Well, according to John Cheney-Lippold’s We Are Data, it is centered on the idea of measurable types. A measurable type is a perceived category that the algorithm puts us into based on our data. These perceived categories are built on thousands and thousands of users data that allows these algorithms to form trends and find similarities between users. These similarities are then broken into categories and each individual is placed into certain categories that they match with. All of this data that you provide these platforms allow them to draw conclusions and create stories based on other people similar to yourself. 
	Over the past thirteen years of inputting my data into the Internet, it’s safe to say that these complex algorithms have built several different stories about myself. One event in particular is my fitness journey that began in December 2015. On December 8, 2015 I searched “How many calories in an egg”, and this is where the narrative started. Ever since I have conducted a significant amount of research about weightlifting, nutrition, and how to take care of your body. For this project I honed in on the first 3 months of this journey. Over the course of these three months I had a pretty even search split between nutritional information on certain foods and types of exercises to help me gain muscle as well as a few searches pertaining to rest and body recovery after exercising. To me, it was clear that I was searching as someone that was a novice weight lifter looking for advice and tips on how to improve. Also, my YouTube history shows several different videos pertaining to proper nutrition and different exercises to perform.
