Coo-production
Artist and Material
In this week's class discussion encompassed the artist, materiality and the cooperation engendered, as a way to look at our practice as a co-production and how to approach with writing. Thus let’s break this down for my artistic practice; What are the materials? How do they impact the work and research? Where is the focus in terms of perspective? I will be looking at this through the three projects I am pursuing this year.
To tackle this exercise it is important to recenter my practice since it has evolved quite drastically in the past 2 years. The main reason I made the jump into the wonders of computing and digital artefact, is to include data into my sculptural practice, so it supports the theory by influencing the visuals.
Brain + Noise + Digital Visualisation:
For my collaboration with Charlotte we are working with the brain background noise as the main material, this influences my approach quite a bit since the data takes a central role in the work. The data contribution is one of size since there are 15 000 values for 1 minute of reading, preferably it also has to be interpreted considering each 128 electrodes that are extracting the signals. Sometimes there are two datasets one for baseline and the other during anaesthesia, these are used as the control group that serve as an example for the people in coma. Thus the work is a research on how to interpret such a large amount of data while making a case for consciousness, then making the data into art and extracting it from it’s numerical grid and experimenting with its temporality. My perspective on this work is deep within the how. Precisely, how to interpret the data visually and how it proves consciousness.
Data + Magnets + Powder:
Next, we have the physical interpretation of EEG data with ferrofluid or steel shaving. In this case the main material is the magnetic property of metal particles. The project can then only take shape by the use of magnets, permanent magnets or electromagnets, the material cannot be activated without it. Before I set out to interpret data, I decided to experiment with the electromagnets and its interaction with the metal. First is the electromagnets, due to the cost and its simplicity, it is way cheaper to make my own from copper wire, steel and 3D printing. This implies that I have total control over my tools as I can decide their magnetic strength and the electromagnet shape to best suit the project needs. Next comes the metal, I will probably use the steel shaving since we have an infinite supply at the metal-shop. I only need to go pick it up once in a while. They will impact the research related to the presentation, in a liquid? out in the open?, within a sculptural work?, using odd shaped electromagnets? as a horizontal/vertical matrix? as motion? For now I am in research and development to find an interesting way to use metal.
Data + Consumer + Power
For transparency the material is web scraped texts translated into an informative visual that the user can use to make a more aware purchase. But to extract the text I need to train a machine learning model that would properly classify them. This tool is of the utmost importance for the first sentiment analysis pass but I need to give it clear instructions on what to look for with reliable training data, and even then, since it is scraping the web who knows what it is going to pick up. For instance when it was launched on a company like Amazon the sentiment analysis showed a lot of good articles… since it is sharing the same name with the forest. There also could be biases within the classification or the sentiment analysis models since they are pre-made packages. At the moment this project also pushed me to take a data visualisation class this semester and a user experience class next semester to fill the gaps I have. For now my focus is on improving the classification model by feeding it proper training data.