Oliver Horsman Art

An exploration from Jan 2021 to the present day:

Digital Degradation: Breaking the Perfection

Digital art seems so final so stuck, so unnatural in the way it doesn’t naturally age and degrade. I wanted to find a way to alter this so I experimented to find ways this could be done. 

I also wanted to find ways that the images could continually change over time. One of the explorations was to exploit aliasing (the graphical computation between two hard edges which enables square pixels to make rounded corners and soft edges) and emphasising the aliased edge. This led me into a technique that produces these diffusion reaction pieces of which “Chroma CMY #1” and “Blue Dot” are part of.

Emergence Through Repetition

The technique I used  was a very simple technique, simply squashing and stretching the pixels and repeating hundreds of times. What started to emerge astounded me, the hard edges started to grow new structures.  What also surprised me was the fact that the underlying colours that made up the work seem to split from each other creating their own pattern. 

I went though multiple experiments using different scaling factors to create differing results. sometimes subtle, sometimes very disruptive. The distortions always emerged where there was the greatest contrast, the biggest differences.

Nature’s Mathematics: The Turing Connection

After spending more time thinking, researching and experimenting I came across the mathematical models of Alan Turing.  Just before he took his life in his early 40s he was working on mathematics to describe how nature creates seemingly random patterns. Stripes on a zebra or spots on a fish, what is it that determines the hue and value of each dot of pigment. Alan Turing came up with an algorithm that could both describe and create these patterns. 

Image from https://www.researchgate.net/figure/Typical-Turing-patterns-of-N-in-model-4-with-parameters-b-0-25-g-0-50-d-1-0_fig2_231021430

Typical Turing patterns of N in model (4) with parameters β = 0 . 25, γ = 0 . 50, d 1 = 0 . 015, d 2 = 1 . 0. Pattern-(a): μ = 0 . 012 248 185 14 ( α = 0 . 70)

https://www.chemistryworld.com/features/turing-patterns/4991.article

Turing’s reaction-diffusion systems mathematically describe how two substances interacting with each other can create stable patterns – like the interplay between an activator chemical that promotes its own production and an inhibitor that suppresses it. This elegant mathematical model helps explain how nature generates patterns like spots, stripes, and other regular formations in biological systems.

I became increasing fascinated with this idea of describing something complicated with a fundamentally simple process and letting it evolve over time.  

Simple Rules, Complex Results

It led me to the question could these fundamental simple processes describe all that we are and have around us?

I did some more digging and came across the work of Stephen Wolfram who had been asking the same question.

Wolfram came up with the idea of Computational Irreducibility its a state in which mathematic algorithms can’t become any simpler.  If you take any process no matter how complicated, then keep reducing the problem into simpler and simpler processes eventually you will get to a state that it can no longer be reduced  (Computational irreducibility).

The Edge of Perception

During this period of exploration, I became fascinated with how our brain’s visual cortex processes edges and patterns. I noticed that when our visual processing system is in different states – such as being very tired, during meditation or with the use of psychedelics – the hard edges of objects can appear to break down into wave-like patterns. These patterns remarkably matched what I was creating with my digital art. The brain’s visual cortex, when operating outside its usual processing mode, seemed to be functioning similarly to my edge aliasing processes, splitting hard edges into offset wave patterns.

This led me more into thinking about how babies see the world. When you play with a very young child, it’s clear they see very differently to us. They don’t have the neural experience to process the world as we do with recognised objects, colours and meaning. They see the world in a far rawer format, they see the world without context.”

Seeing Without Context

This led me more into thinking about how as babies we see the world. When you play with a very young child, it’s clear they see very differently to us. They don’t have the neural experience to process the world as we do with recognised objects colours and meaning. They see the world in a far rawer format, they see the world without context. 

Could an adult brain relaxed through psychedelics be breaking down the neural pre-context it has learnt through it’s life and in doing so start to see the world like a baby again?

Cultural Colors

As adults  so much of our experience are automatic, for example: we group different hues and shades of colours into names, in doing so we remove a lot of our ability to see new colours. For a modern western brain – plants are green. In other more indigenous cultures that rely more heavily on plants for their survival such as the Namibian Himbas they have many more ways of describing green. For them it could mean life and death eating from a plant that is the wrong colour. Their visual cortex can differentiate many more shades and hues of green. 

https://gondwana-collection.com/blog/how-do-namibian-himbas-see-colour

Fundamental Patterns

This persuit to find the root cause of how a pattern in our macroscopic world might have formed has inevitably led me to the quantum world and to look at some of the smallest most fundamental structures in nature – quantum fields (wave-like structures that permeate space and evolve through time)

https://bigthink.com/starts-with-a-bang/this-is-why-quantum-field-theory-is-more-fundamental-than-quantum-mechanics

https://bigthink.com/wp-content/uploads/2019/05/1GptWg3QM1RtAZMBasNg_SA.gif?resize=480,270

The Fundamental Question

So by unpacking a hard edge on a digital image and running an incredibly simple repeatable process (squash and stretch) on it, are we seeing what these fundamental systems could look like?!

Here’s a gallery of some other experiments I have had: