My masters in Digital Arts and Humanities at UCC taught me a lot about creative applications for technology. In our History and Theory of Digital Art module we were tasked with creating digital art. Digital Distortion is a commentary on how we represent ourselves on social media. Everything we put up is carefully curated by ourselves with our digital selves ending up much further away from our actual selves. To represent this I chose to put my own image through a number of processes both digital and analogue until almost unrecognisable and use as many of my own digital image processing skills as possible.
ART LINK: https://youtu.be/7P0gkptT2LY [Turn on closed captions]
CODE LINK: https://github.com/nic-name/glitch-art
Using a geometric patterned background, I took a large amount of “selfies” as an homage to the popular social media technique. The background image used is deliberately unnatural to further show how we are distorted on social media. All of the selfies were then heavily filtered to the same level as my social media pictures. Angles were carefully chosen to display my social self in the best possible light. I included one picture taken through a mirror to analogise self-reflection – when you look at your social media self you see it in black and white and can be aware of the distortion but blinded by the beauty of this carefully curated self.
I used three separate means to create the glitch, Notepad++, Audacity, and a bespoke Python glitch program that I wrote myself for this project.
Analogue: The piece Analogue was created using Notepad++, the image was converted into a RAW file and then opened as a .txt file in Notepad++. Data was deleted, copied and pasted, added, until a desired glitch effect was noticed.
Echo: The piece Echo was created using sound engineering software Audacity. The RAW file was imported into the software and an echo filter was applied to the resulting “audio” waves that were generated by the import.
Faces: The piece Faces was also created using Audacity, this time multiple filters were applied to the RAW file before it was then exported and converted back into a JPEG.
Algorithm: Algorithm was created by me using Python. I wrote a program imageprocessing.py that takes in an image that contains an algorithm that selects a random array of pixels and places them in another random location creating a glitch effect.
Inversion: Inversion was created using another method in the imageprocessing.py program I wrote. This takes all the RGB values of a pixel and inverts them to create the colour effect. I also applied the same effect used in the piece Algorithm for further distortion
Grey: Grey, a method in imageprocessing.py takes all the RGB values of a pixel and divides them by 3, creating a grayscale effect. I also applied the same effect used in the piece Algorithm for further distortion.
I converted my own images into sound, using the RAW files of the images to create a sonic landscape for my art. All sounds are made using clips from my own photos which were further distorted in Audacity using effects.