Seeing in Color
"The manual training school, comprising a full statement of its aims, methods, and results, with figured drawings of shop exercises in woods and metals" (1906)
Much has been said about the way machines will augment us, help us do more, think faster and in new ways.
But that is only half of the picture.
There is a fallacy in the thought that this relationship only goes one way. That the more technology we build – the more we extend our external systems, businesses and tools.
A system is more than an iPhone. It is an iPhone plus your brain. And your cognition, your mind, your emotions and anything else that reconstructs the world for you. And as technological innovations are tools are part of the environment, as they change so does your mind.
Once we accept this premise we can move onto the next step of this, autonomous processes.
Our jobs consist of tasks, things we do day in day out. Some of these tasks are structured and ready to be automated, and some distinctly human – like knowing when to smile when meeting a client.
As more of these pass on to machines, the more cognitive surplus we’re left with. This new reality is challenging and holds the possibility of a tipping point where a machine can perform a meaningful majority of the tasks a human does, let’s call it the Turing test of employment. When that happens it is both unfortunate, and avoidable.
I argue that machine have already won the optimization battle, with one crucial caveat. It sees the world in a single color, monotone.
We human are all born with innately multidimensional perception of reality. We receive the world by symbols and representations, and not by numbers.
This full color view is innately, categorically and unequivocally human. Machines operate by black and white averages, nothing more and nothing else.
Decades of being told what to do, rule based Taylorism and segmented systems faded some of our color sensors. Being a human is not as straightforward as it used to be.