This article was published first on ArtsCabinet.
So, what makes “Art” art?
A timeless question that has animated many arguments over the last 40,000 years as we found countless ways to express ideas and explore the human condition.
Given the complexity of the question, I choose to answer by taking a side that presents the growing artistic movement I belong to: Data Art.
In one sentence, Data Art uses facts, information or statistics about a phenomenon to drive the artistic representation. It stems from generative art and data visualizations and can be classified in the broad category of new media art.
In more simple words, we could say that data art tries to translate an Excel spreadsheet’s rows and columns into a visual representation that is hopefully aesthetically pleasing to the eye. It has a scientific component wrapped into an artistic representation.
The fact that it is based on real data adds a unique and interesting layer of meaning to the piece. To make a statement, for the first time in the history of art, the very fabric of an artwork is based on genuine facts and an “objective” measure of something, rather than solely on a representation of the artist’s subjective view. Of course, I put objective in quotation marks because the data we collect is always subject to a form of bias (Khosla et al. – 2012 – Undoing the Damage of Dataset Bias) and can never be purely impartial.
Even though a data artwork relies on algorithms, its final representation is not limited to digital imagery; it also encompasses the same spectrum as other art forms. A quick Google search will reveal physical data sculptures, paintings, printed pieces, music, or even data-driven dances.
Why does it matter?
The intrigued reader can wonder why Data Art has yet to take the (art) world by storm…
First, I think that the discipline is still in its infancy and that it needs to attract more practitioners to become mainstream. Second, because it is rooted in technology and science, part of its appreciation comes from our general scientific literacy in itself.
Unfortunately, subjects like Big Data, Artificial Intelligence, Quantum computing, Blockchain are over-hyped by zealot journalists and rarely discussed rationally with the right level of detail. As a result, we can be scared, especially when we only hear about the dark side of technology (for instance Netflix’s Blackmirror).
Data Art acts as a counterweight to these fast-paced articles. It invites us to look at data from an unexpected angle: the emotions. Once the hook is in place, it lets us process the information with our rational side. The principal difficulty for the artist is to find the right balance between science and art.
Measuring the impact of data (art)
I assume that most artists have a desire to be understood. As a data artist, one of my struggles is to ensure that the underlying message behind the piece is clear and that the data plays an essential role in helping the audience question itself.
As a scientist, I could not resist asking for feedback around me to see if this was actually the case. I started looking at the scientific literature to see if others were also interested in quantifying the impact of art on people. Fortunately, the emerging field of Aesthetics Research is dedicated to the study of art appreciation using scientific methods (Can science account for taste? Psychological insights into art appreciation by Annukka K. Lindell & Julia Mueller 2011).
One of its cornerstone papers found that to the untrained eye, the subject matter, technique, or colors seemed to be the most important. On the contrary, the art-trained viewer pays more attention to the overall composition and the deeper meaning of a piece. (The Role of Formal Art Training on Perception and Aesthetic Judgment of Art Compositions by C.F. Nodine, P.J. Locher, E.A. Krupinski 1993)
It seems that beauty is either in the eye or the mind of the beholder!
For the specific case of “data art appreciation”, everything is yet to be done. Fortunately, it opens very interesting research perspectives and would definitely benefit from your feedback!
Over the next few months, I will try to gather the maximum number of opinions on the perception that you have on a few selected pieces of data art. I will then write a follow-up article to explain and discuss the results.
I hope this short post got you interested in the amazing world of data-driven art. If you have any comments or feedback, please leave a message below.