There are a few recurring themes in this course. One being “everything is not as it appears”. Weeks 8 through 12 explore the various ways in which connections are made in the relatively new (to language and literacy, anyways) digital world. The Web has taken on new meaning for me. As written in week 9, “ The web is content—a network of interconnected digital documents that use hyperlinks and metadata to establish such connections.” I mean, it’s literally a web of endless connections! Like a spider’s web! Huh, how about that? Out of this web of networks and hypertexts are born predictive algorithms that are meant to process data and give us predicted outcomes. The simple algorithms of predictive text on our phones are a small-scale example of what algorithms do.

I chose to link task 11 to Ian Lee’s blog post. I was interested in how he shared the predictive text of the selected, left, center and middle words on his device. My initial understanding of the assignment was to only select the middle predictions, which is what I decided to share in my own blog post. Interestingly, Ian experienced something similar to me (which I didn’t share in my reflection) where the middle predictive text option would lead to endless loops of the same sentence over and over again.  The middle seems to use the most frequently typed words following a certain other word. I also noticed a similar trend as Ian pointed out, when you add punctuation, the predictions become even more cyclic. If you add a period, it will always begin the new sentence with the most used first word, in his case, it was I, and thus begins the same sentence over and over again. When imagining a web of connections and algorithms that are based on calculations of trends, I think it’s easy enough to understand how a feedback loop happens causing a cyclic and repetitive outcome that doesn’t have any true meaning. It’s a simple example of why algorithms will never be perfect.

I related to Ian’s conclusion where he noted the importance of taking technology slow and reflecting frequently. I have a similar sentiment where these tasks have made me realize that we do need to speculate everything. The Web is vast and complicated and meaning cannot always be derived from calculated predictions. It kind of overlooks the depth we have as humans and just skims the surface of what is observable. So it’s very important to stay vigilant and keep the humanity in trying to understand the Web.