Machine Learning & Visual Rhetoric
Machine learning is a concept on everyone’s mind in todays world. In the past, movies such as The Terminator and 2001: A Space Odyssey have influenced the minds of many, foreshadowing the dangers of automated intelligence. But these bleak outlooks on the future have long since been overshadowed by technological advances such as Siri and Cortana. Many don’t even realize this technology is a shining example of advancements in machine learning, and they’re only going to become more frequent. Technology has radically altered the way we view and read media, and forward thinkers and engineers are eager to push the boundaries even further. Visual rhetoric has been essential to the development of communication and advances in the way we see and understand visuals is ever-evolving. Machine learning will affect visual rhetoric, it already has, and there is only a matter of time before we start to see even greater changes.
So, what is machine learning? Machine learning is, in the simplest form, a subset of computer science where machines are being programmed not to be programmed. This is a bit circular, but it goes like this: An engineer programs a small four-wheeled machine to pick up a square block within a pile of shapes and put it in a bin. Without further programming, the machine executes the task, but it isn’t finished there. The machine then goes on to recognize which objects are and aren’t square blocks and puts them in the bin. This would be an example of machine learning; the machine understood the task and used deductive reasoning to solve the problem. There are three main types of machine learning: supervised, unsupervised, and reinforcement learning. Supervised learning involves human interaction where inputs are given to a machine that must determine a pattern to understand outputs. Unsupervised learning is similar, without human interaction or input; this is the most challenging subset of machine learning. Lastly, reinforcement learning is, for example, self-driving cars like the Mercedes S550 and Audi A7 and A8. Here, the machine is reinforced by sensor inputs from surrounding vehicles and learns the shape of the road through sonar-esk procedures. The examples of machine learning in our society are endless; there are far too many to count. At this point, we are surrounded by machines, some which build our ships, others our cars, phones, and household items. The new advance is to take these ordinary machines and move them into the realm of cognition.
Visual rhetoric and technology go hand in hand because the way we often view visuals in the modern era involves technology and these two industries are intertwined and constantly impact each other. Information graphics are often generated with computers and displayed on computers or by them. Inherently, the ways we display visuals is impacted by the platform we have the ability to share them on, and vise-versa. With improvements in technology, there can also be improvements in what can be done with it. Examples of this would be the evolution of Microsoft PowerPoint to websites like Prezi, where the user has a more immersive, interactive experience for the viewer.]
What is going to change? Just about everything. It is hard to hammer down specifics on what machine learning is going to alter, however, one can be certain that targeted advertisements will become more prevalent as machines continue to learn our preferences of where we shop and what we do. Interactive interfaces will become more commonplace, where the interface may not only be interactive, but also be designed for the individual by the machine. We will start to experience evolution in the way we view videos, where we go to view them, and how many steps it takes to get there. In other words, simplification. Where machines can begin to take the labor/thought intensive processes from humans, we will begin to live simpler lives because the machines have the ability tobear our burdens.
Visual rhetoric and machine learning is at the forefront of technological advancement. The changes are happening, and they’re happening now. The differences we will see in the way we experience our digital world are profound, and they’re leaking into the way we view traditional media such as books and poems as well. Where we once had text, we will now have information graphics. Where there was once vivid visual descriptions of a setting, we will now have a picture. Visual rhetoric is evolving: the changes are here, and they’re here to stay.