TL:DR
- Data Art, emerging as a unique fusion of Generative Art and Data Visualization, represents a significant evolution in the art world, where artists utilize external data in their creative process.
- Unlike Generative Art, which often emphasizes the final product over the rules guiding its creation, Data Art intricately intertwines both the process and the outcome.
- This art form leans more towards provoking questions and evoking awe rather than just offering clear-cut information or answers, marking a shift in how artists interpret and present the complexities of the world.
The arts have always been a tool for humankind’s grappling with understanding the world — whether it be the weather, the animal world, the complexities of human relationships, or the innermost depths of the psyche. It started with mythologies and religions, represented through poetry, song, painting, and sculpture, and evolved into ever more complex belief systems and art forms.
But thanks to globalization, the scope of human concern has ballooned out from our immediate sphere of influence to include far-flung wars, environmental collapse, political upheaval, social unrest, and…whew, the list really goes on.
It’s then no surprise to see artists making sense of the world using more sophisticated tools of understanding, namely data, the modern world’s chief method of deciphering ourselves and the world around us.
As network scientist Albert-László Barabási wrote in an op-ed penned for ArtNet in 2022:
“The evolving social, economic, and technological factors that define our existence today are way too interconnected and far too complex for any single individual to grasp. To apprehend and respond to this reality, art must co-opt the tools that science, business, design, manufacturing, and politics have long adopted to engage with the world and spur change.”
Data Art (or, as Barabási calls it, Dataism) sits in the spectrum between Generative Art and Data Visualization, though there is much overlap and gray area.
Where Generative Art relies on random or at least insular rules for creating work, Data Art pulls information from the outside world into its creative process. Most often, Generative Art emphasizes the outcome over the rules-based process. With Data Art, process and outcome are inseparable.
Where Data Visualization seeks to make information clear-cut and understandable, Data Art leans on art’s propensity for posing questions instead of providing answers and for provoking awe over comprehension. That said, some artists working with data lean heavily on delivering a message, while others leave things more open-ended.
Take for instance one of the earliest examples of Data Art: On Kawara’s Today series, which comprises nearly 3,000 monochromatic paintings inscribed with the date of their creation and nothing more, which the artist created from 1966 to 2013.
Taken together (if you’re so lucky to see an exhibition) the series inspires a new appreciation of time, curiosity at the discipline such a feat requires, wonderment at the simultaneous enormity and finitude of a human lifespan, and quite likely much more.
In a recent interview I did with artist Brendan Dawes, Dawes recounted a project he’d worked on for Google that took a lot of on-paper ideation. When the project was done, he emptied his pencil sharpener onto his work desk; the long, thin pile he created with the pencil shavings, according to Dawes, was an example of data representing the project he’d just completed.
Similarly, Angela Haseltine Pozzi and her Washed Ashore project could be seen as taking a unique approach to “data” in the way Dawes describes it. The Washed Ashore project gathers trash from the ocean and uses it to build sea life sculptures. Seeing the scale and detail of these artworks bends the mind toward understanding just how much damage humankind is doing to the planet’s oceans and waterways.
In a more scientifically rigorous manner, sculptor Nathalie Miebach weaves baskets to represent changing climate patterns, natural disasters, and environmental catastrophes.
Where some data art wishes to describe, probe, or educate, others seek to intervene, as Alexandra Daisy Ginsberg’s Pollinator Pathmaker does.
To address the complex challenge of maximizing pollinator diversity, Ginsberg collaborated with experts to create an algorithm-based living artwork that designs gardens with empathy, focusing on supporting a wide range of pollinator species by selecting and arranging plants according to their visitors’ varying preferences.
For the first “edition” of the work, Ginsberg and team planted along a 55-meter stretch of land at Cornwall’s Eden Project. After inputting information about their gardens, collectors can generate their own garden designs, which come with free planting instructions and a certificate of authenticity, all with the aim to create a comely host for swarms of pollinators.
Looking at a different kind of swarm, Spanish artist Xavi Bou’s ongoing Ornithographies project presents a unique photographic approach to capturing birds in flight. By stitching together thousands of rapid-fire images, he creates abstract visuals that convey the fluid motion and energy of birds, from the erratic movements of Alpine Swifts to the smooth patterns of gulls.
Expanding into video with Murmurations, Bou showcases starlings evading a hawk. This animation, requiring extensive post-production work, captures the interplay between predator and prey as a dance, creating fleeting aerial sculptures.
After watching the above video, you may very well feel awe at the sweeping intricacies of bird movements, but there are much greater enormities that artists can unfold using data.
Wylie Overstreet and Alex Gorosh used LED lights spread 4.3 miles across a dry Majove lakebed in proportion to milestones in the 13.8 trillion-year history of the universe to give visitors some scope of the age of time itself.
As Overstreet says in the opening of the short documentary about the project:
“Every human being understands time as seconds and minutes and hours and years. But our brains are not wired to grasp how old the universe is… If you want to understand the age of the universe, you have to see a scale model of time. And the only way to see it is to build it.”
I’d be remiss if I failed to mention the current art world darling of Data Art, Refik Anadol. Rather than describe his much-ballyhooed MoMA installation, Unsupervised, I’ll highlight a prior project designed for Berlin’s KÖNIG GALERIE: MACHINE HALLUCINATIONS — NATURE DREAMS.
This monumental data sculpture was created using a dataset of over 300 million publicly available images of nature, which was then used to train a Generative Adversarial Network (GAN) AI algorithm.
Nature Dreams transformed the dataset into a unique multi-sensory experience, encapsulating the essence of nature as perceived by artificial intelligence. The sculpture presented pigments, shapes, and patterns typically associated with nature, yet these elements existed solely as constructs of the machine’s “dreams.” This blend of AI and art not only commemorated the beauty of the natural world but also explored the nuances of artificial intelligence and its ability to reinterpret and represent the natural environment in a synesthetic and surreal form.
In my interview with Christian Burke, Lead Data Scientist at Refik Anadol Studio, he called out a moment at the KÖNIG GALERIE as the most profound reaction to an Anadol piece he’d ever witnessed:
“A couple who had lost a loved one recently was sitting there. They had such an intense reaction that they were crying together, appreciating the artwork, and feeling the emotions. It was a profoundly sad and beautiful moment.”
By pulling in the world around us and then representing it back to us, Data Art does something more profound than making sense of the world or making pretty pictures; it it ignites a dialogue between the viewer and the vastness of existence.
