The increase in the popularity and use of data is a reflection of people’s need for visible evidence, rather than just being told something is the way it is. Data is just an illustration of words. It is words put in to simpler context that is much easier to understand. However, data completely replacing words does not seem like the positive route it has been laid out to be. When we replace words with data, we loose the capacity for contextual meaning. It is true that words can be misleading, but so can data.

“Data” is everywhere today. Almost every field of study deals with data and if there is no data, the study is not considered reliable. It is interesting to think that in the past, data was not necessary to prove a point. One could just say that something was the way it is and people would believe them. Obviously there are limits to this power, but it is much harder to pull that off today. People need data, or evidence, to believe a claim and take it as fact. We have become so dependent on data to separate truth from fiction, that we may have become blind to its downfalls.

It is clear from Professor Aaron Hanlon’s lecture that words can be misleading. If a picture is worth a thousand words, then it can be a thousand misleading words. Just because there is a picture, does not mean what is being portrayed is accurate. When it comes to art, especially photographs, framing is extremely important for context. We think photographs to be concrete proof with no bias, but it is very easy to manipulate a photograph to portray what the photographer wants. This is true of illustrations, and it is true of data.

It is important to keep in mind that the data presented is going to be biased based on who is presenting it. There is a reason for particular uses of data, and data can be manipulated to reflect the intention of the presenter. Another point from Professor Hanlon’s lecture was that meaning requires context. There are multiple ways to interpret a statement, so one needs some background to infer the correct meaning. This applies to data in the sense that it needs context in order for those interpreting it to make the right connections. In many cases, words are required to help provide this foreground and form the context.

A conclusion from this lecture was that when data becomes the main form of evidence that will be revolutionary. But are there questions that cannot be answered with data? I would argue that yes, not everything can be proven with data. There are other ways to present information and prove findings that are better than data in certain context. Relying solely on data as evidence is irresponsible. I am not saying data is bad. Data is great, but it should not be the method of evidence used. Yes it would be revolutionary for data to become our main form of evidence, but that does not make it the best option.