Everytime I think about our future, I am hopeful for what it holds. I think about my girls, all grown up, in a world that chooses selflessness over selfishness and to spread kindness whenever possible. I hope my girls use the power of technology to connect to and learn from others, while embracing the diversity that exists around them. 

When was the last time you opened the front door to grab the daily newspaper and flipped through to your favourite section while getting black ink on your hands? It’s more likely that you unlock your phones to open an app, like Twitter, and begin to scroll through the newsfeed as you read updates. How we consume and produce information has changed over the years. I am frequently checking my Instagram account (more than I’d like to admit) and find much of my parenting information on the platform by following experts in the field. The IG algorithm also ensures that more of these similar accounts show up on my feed and I am able to read a compact amount of information in a shorter period of time.  These short statements are typically used on social media platforms to share  personal opinions or experiences. These microblogs have exacerbated the need to constantly share and post about our everyday doings- from taking pictures of our food to tagging our location. I would ask, is it really necessary? By condensing our thoughts into these bite-sized captions, often accompanied by a # or picture, it limits the in depth conversations and analysis, focusing on the entertainment value and the number of likes rather than the content itself. In this regard, I think it alters the way we write, as we want to be perceived in a certain light or to capture a wider audience- adding emojis to make it more light-hearted or tagging a friend/ company to receive a response. Moreso, predictive text takes away some agency over the writing process as it guides the sentence structure and selects the next word to resemble your voice. 

When I was generating my post on IG, the  software was able to correct my spelling errors (notably,  separating the words every-time) and predict a few of my words. Interestingly, as I was typing out the first few letters, it was able to predict the root word but not in the correct grammatical sense. For example, the word ‘hopeful’ came out as ‘hoping’, suggesting that my sentence would continue. Based on the context of the statement, the software was able to decipher my thoughts by drawing from hundreds of words and phrases that were used in the past. Since I used my iPhone for this task, there could also be an abundance of data drawn from a larger dataset from other Apple devices. 

In terms of other textual products, I would argue that these statements are not commonly found in academic articles or novels, it is more likely to find such writings in magazines. That being said, there is potential for algorithms to be used in those contexts in a way that captures the specific topics by selecting from a more discrete data set.  As AI systems learn personal typing patterns, it has the potential to streamline work and to improve productivity. Moreso, for education, this algorithmic technology used to predict text can assist students in writing tasks, particularly for those students who may struggle to start generating ideas by making the process less frustrating. These deep learning software have the potential to become more adaptive with the context and more accurate with its capabilities to target domains by suggesting certain words.