Professor Aaron R. Hanlon, Assistant Professor of English at Colby College, gave an extremely compelling lecture about data. His main hypothesis is that data is extremely easy to mistake, misrepresent, and ultimately misconstrue. His focus on the importance of recognizing the validity of data was extremely compelling. Professor Hanlon was able to demonstrate the importance of data overall. He encourages scholars to think about where their data is sourced from and how that will impact the conclusions that they make regarding the data.

As a double major of Environmental Science and Biology, data collection and interpretation is something that is not foreign to me. Personally, I found that Professor Hanlon’s talk was influential because in some ways it had undermined my immediate understanding about the importance of data and what it represented. My understanding of unbiased data was very different from Professor Hanlon’s. His approach towards data was much more cynical than I think I had ever been. That being said, I think his cynicism was completely justified. During his talk I realized that a lot of the data that I had been exposed to, I had oftentimes just accepted with little to no questioning.

I am currently in a Statistics class, which is largely focused on the collection and statistical interpretation of data. Interestingly enough, I have found that a lot of what I’ve learned in my Statistics class coincided with what Professor Hanlon had to say about data. Despite this being an interesting overlap of academic disciplines, I found that this dual confirmation helped me to solidify my understanding of data collection practices. Unbiased data is crucial for the accurate representation of the truth.

Contrary to the idea of the truth would be the consequences of what happens if data is misrepresented. Professor Hanlon stresses the weight that data can carry in a person’s understanding of any given topic. If misrepresented, data has the potential to sway audiences to wholeheartedly believe in a falsity. This concept reminded me of Professor Judy Stone’s talk on how the misrepresentation of scientific findings lead the public to believe in a biological definition of “race”. Professor Judy Stone’s example demonstrates how the misrepresentation and misunderstanding of data can fuel larger social issues like racism.

Upon reflection on Professor Hanlon’s talk, I’ve come to find that I have a completely new understanding of data and how it can ultimately impact the way we view the world around us. It is extremely powerful in altering one’s way of thinking. For this reason, it is crucial that data be correctly gathered and accurately depicted. Professor Hanlon revolutionized my previous understanding of data. His ideas and methods will definitely carry with me and be applied into my majors.