You’ll recall, a few months ago, when Google made it possible for all of your Facebook friends to find their doppelgängers in art history. As so often with that particular company, the fun distraction came as the tip of a research-and-development-intensive iceberg, and they’ve revealed the next layer in the form of three artificial intelligence-driven experiments that allow us to navigate and find connections among huge swaths of visual culture with unprecedented ease.
Google’s new Art Palette, as explained in the video at the top of the post, allows you to search for works of art held in “collections from over 1500 cultural institutions,” not just by artist or movement or theme but by color palette.
You can specify a color set, take a picture with your phone’s camera to use the colors around you, or even go with a random set of five colors to take you to new artistic realms entirely.
Admittedly, scrolling through the hundreds of chromatically similar works of art from all throughout history and across the world can at first feel a little uncanny, like walking into one of those houses whose occupant has shelved their books by color. But a variety of promising uses will immediately come to mind, especially for those professionally involved in the aesthetic fields. Famously color-loving, art-inspired fashion designer Paul Smith, for instance, appears in another promotional video describing how he’d use Art Palette: he’d “start off with the colors that I’ve selected for that season, and then through the app look at those colors and see what gets thrown up.”
In collaboration with the Museum of Modern Art, Google’s Art Recognizer, the second of these experiments, uses machine learning to find particular works of art as they’ve variously appeared over decades and decades of exhibition. “We had recently launched 30,000 installation images online, all the way back to 1929,” says MoMA Digital Media Director Shannon Darrough in the video above. But since “those images didn’t contain any information about the actual works in them,” it presented the opportunity to use machine learning to train a system to recognize the works on display in the images, which, in the words of Google Arts and Culture Lab’s Freya Murray, “turned a repository of images into a searchable archive.”
The formidable photographic holdings of Life magazine, which documented human affairs with characteristically vivid photojournalism for a big chunk of the twentieth century, made for a similarly enticing trove of machine-learnable material. “Life magazine is one of the most iconic publications in history,” says Murray in the video above. “Life Tags is an experiment that organizes Life magazine’s archives into an interactive encyclopedia,” letting you browse by every tag from “Austin-Healey” to “Electronics” to “Livestock” to “Wrestling” and many more besides. Google’s investment in artificial intelligence has made the history of Life searchable. How much longer, one wonders, before it makes the history of life searchable?
Based in Seoul, Colin Marshall writes and broadcasts on cities and culture. His projects include the book The Stateless City: a Walk through 21st-Century Los Angeles and the video series The City in Cinema. Follow him on Twitter at @colinmarshall or on Facebook.