Humans have an often-praised tendency of being explorative and curious about the surrounding world, but it often goes unnoticed that this quality is nothing but a consequence of a greater underlying need; an urge to subdivide the outside world into separable parts in order to grasp it and seize it as a whole.
This is how humans have approached the physics of living beings, by opening up animal stomachs to study their intestines, dissecting muscles to examine the cells under a microscope, and performing autopsies of cadavers to clarify and isolate causes of death.
Likewise, we force our surroundings into separating structures, most often sectioning it in the shape of a grid. Vertical and horizontal lines crop mountains, lakes, meadows, cities and oceans into squares on maps, which again are subdivided into smaller squares and so forth. Like the map, the pixelated digital image is also divided in such grid. The more pixels an image has, the more individual parts it contains, which then creates a more accurate image. But even the pixelated image is just a cube in a larger mosaic, a small pixel in the algorithms’ thousand-eyed image analyses. Algorithms offer the human desire for dissection an infinite perspective, because they guarantee that no matter how many elements we may wish to pulverize the world into, it will always be possible to recollect them and shape them into a perceived meaning. It proves that not even the limitations of the human cognition barricades how fine we can dissect our surroundings with the aim of dominating it.