We didn’t collect data about people that we didn’t know or weren’t close with so the range of personalities were definitely limited. A lot of the Myer Briggs personalities we collected were pretty similar too because it’s more common to befriend people that were the same. I think we became more intimate with our data because the range wasn’t too big and it was just our circle of friends, family and roommates. In "The Greatest Number” by Adam Florin and Theodore Porter, they mention “...standardization presents many difficulties, and is not always welcome: You get resistance from people who prefer not to classify or be classified entirely through data.” I connect with this excerpt because some of my friends believed that the personality test they took wasn’t accurate to who they really were but just how they were in the moment. It feels weird to be identified in numbers and I personally don’t trust the Myer Briggs and prefer to identify myself by my own rules. This also connects to Mimi Onuoha’s talk “How We Became Machine Readable”. She mentions how in minorities we not included in a lot of datasets because they are seen as outliers and these people cannot be classified or represented in data sets because of biases and fear of inaccuracy.