Oh Sweet Randomness! If we can achieve true randomness by cleansing our production environment of all bias, && if a bias-free state signifies authenticity, then I guess to be truly random is to be truly authentic.

There is no absolute chance or random event, for chance and randomness are aspects of the way in which we structure our universe.

Randomness is recursive, like a fractal. It’s easy to think of randomness as chaos, but this entropy is the very constant that keeps the universe in balance. To be random is to operate at the scale of the smallest organism, and maybe the biggest miracle. To strip yourself of bias is to take the form of pure democracy, a collectivized whole made up of microscopic particles whose diverse energy preserves their unity, thanks to the lack of hierarchy or order within their networks: the individual moves freely, recklessly, liberated from any desperate pursuit of individuality. Randomness is the behavior that we might as well practice like magic. A room full of bodies, dancing and dancing—bounce off one another, a truly inexhaustible circuit of energy. All painting the floor with the texture of their breath and sweat, they move in tandem—appearing synchronized the same way that the stars do in a dark night sky, or blades of grass while you’re perched on a high tree branch. True randomness is when you zoom all the way out, enough see the bigger picture, and you can confirm that its totality is comprised of the glossy, smooth texture of a perfectly recursive pattern, thanks to random behavior.
It’s not so easy to practice this magic, just as it’s not so easy to see the bigger picture. You can never know where the true edge of the image lies. It is so big that perhaps it belongs to another dimension, one beyond our comprehension, even if your brain lazily urges you otherwise. What’s much more palatable, enticingly visible, is the pseudo-randomness, the simulation of randomness. Achieving a simulation of randomness is not the same as achieving randomness. This is where the danger creeps in: if a pseudo-random weight is used to train a machine-learning model to detect outliers from a pattern, then the model may never be able to reach a high level of accuracy. If I pour paint on a canvas and it happens to fall in a way that appears exquisite in its aura of chance, in its aura I will get stuck like a fly drawn to honey—if I’m not careful. A simulation of randomness—an impostor—is easy to believe. When we lack the literacy to see, comprehend, rewire the system that generated it, because we gave up on that literacy long before we were even born, we cannot grasp the scale of the plane it inhabits. And why should we, when pseudo-randomness serves us so well?
Perhaps to first recognize that we will never design in a vaccuum, our hands and our not-so-precious content alike will never be totally free of bias, and thus our design will never aspire to perfect randomness, is a step in the right direction. We may find a small (or big) weight lifted off our shoulders when we acknowledge the constraints of the present, to design within these parameters. If semiotics run the world, we may as well run with the right signifiers.