My view of art online has been strongly shaped and influenced by the fact that I spent over eight years working at Artsy, which is considered one of the art world’s most influential online platforms. Artsy is both a website (artsy.net) and an iPhone app used for collecting and discovering art. Its stated mission is ‘to expand the art market to support more artists and art in the world’.
In the tradition of other American start-up origin stories like that of Facebook, where an enterprising and ambitious young person identifies a need for something and then builds it in their dorm room, Artsy started out as an idea in the head (and then the dorm room) of Princeton University student Carter Cleveland. Born and raised in New York City, Washington, DC and London, Cleveland was a computer science major with an interest in art history (his father was an art writer and collector). He wanted to put original art on his dorm room walls rather than posters, but he couldn’t find a place on the web to connect with younger artists to buy their work in order to make this a reality. So Cleveland built a website called Exhibytes, which he intended as a social platform for young artists. He thought artists would post their work there and use the site to socially network (as the creative community uses Facebook and Instagram today), and in doing so provide an opportunity for people to buy their work online. It would be a great replacement for the posters he didn’t want to have, and would serve as an accessible way to connect with young artists.
Unfortunately, Exhibytes didn’t work out so well. The upside was that the idea was good enough for Cleveland to win some business grant award money from Princeton to develop it, but the downside was that artists didn’t use the site. Most importantly, it seemed artists didn’t want to socially network there as they had on Facebook and other platforms.
Like any talented entrepreneur, Cleveland digested this feedback and data and then pivoted. He became interested in the idea of developing a ‘genome’ for art, based on what the music website (and now app) Pandora had done with its Music Genome Project. His thinking was that this could be an exciting and new way for people to engage with art: users would be able to, as on Pandora’s site, key in the name of an artist they knew, and get tailored recommendations. In so doing they would expand their knowledge of art, and eventually they might even buy something. It had the potential to be an ideal combination of art education and collecting, and it promised something that really didn’t exist in the art world – because at the time, searching online for art and getting intelligent recommendations was quite difficult. Google searches could only bring up artists’ names and movements; quality control was poor, and the images were not consistently good. Museum websites offered only limited search capabilities. And there was no one-stop shop for the world’s art – art existed all over the internet, on gallery and museum websites, but nothing knitted them together. The existing resources for aggregating art worked only on historical art or contemporary art, never bringing the two into one space.
With this idea of an art genome in mind, Cleveland reached out to Pandora’s CEO, Joe Kennedy (who was also a Princeton computer science alum), and asked if there was any issue with him pursuing it. Kennedy gave his blessing, and so Cleveland began developing what would eventually become Artsy. He tried to buy the domain Artsy.com, but the price was too high, so instead he picked Art.sy. At that time, site names divided by dots were in vogue; more importantly, it gave the site the shortest possible domain name with ‘art’ in it. Artsy, like Pandora, was ‘powered by The Art Genome Project’. I came to Artsy serendipitously at the beginning of 2011, about a year before the site had launched.
For the next four years, as director of The Art Genome Project, I led a team of people to create a genome for art. The project (we internally referred to it as TAGP) was initially inspired by Pandora’s processes. These were to create a list of possible attributes for pieces of music – such as genre, beats per minute, vocals; basically anything you could think of to describe music – and then go through musical pieces and rate them for these attributes, so when you were done you would be creating a list of attributes (‘genes’) for each piece of music that would comprise something like its ‘genome’. There would also be genomes created for each musician, apart from their individual songs, since a general search for The Beatles should bring up the diversity of what they produced, an aggregate sense of who they are; but each song could be given quite different genomes to account for their differences.
Also, for Pandora, genes were importantly not tags, or things that are binary (you are either tagged in a photo or not; you are either tagging a location or not) but could be given strengths from 0 to 100, to rate the strength of the connection of the gene to the musical piece. This range allowed for a significant amount of nuance and a much more detailed way to connect musical pieces with each other, which was important over time, especially as their database got bigger. What this data set worked out to for the user was that through an algorithm on the back end of the site that located similar genomes, they were able to (on the front end) be recommended an artist or a piece of music based on whatever they input into Pandora’s website, and learn about new music even if what they knew themselves was quite limited.
At Artsy, we took an approach similar to Pandora’s. We created a list of all the attributes that you could apply to art (for all art, but in practice it was much more tilted to contemporary art, reflecting the focus of the site); and then we spent a great deal of time applying these terms to the site’s artists and artworks, whose numbers started to rapidly increase as we established relationships with galleries, museums and image rights societies. (Importantly, all of the images we posted to the site were used with permission, not ‘scraped’ from the web.) As with Pandora’s technology, we were able to provide nuance to the genes and not just tag artworks. This allowed for simultaneous similarities to happen – something could have many connections at once. When you searched for an artist, you were given a list of multiple artists – not just one; the same thing happened with artworks, and these lists presented a range of ways in which art and artists might be similar, from formal characteristics to more conceptual qualities.
Because we personally were creating recommendations for potentially millions of people around the world, we consistently acknowledged the subjectivity of the project. We knew that another group working in the same way might have created an altogether different genome; and we knew that the project might have been undertaken in a different way a few years earlier or later. But we had confidence in our art-historical and art world expertise. The overriding concept was that this would be a jumping-off point for learning about art, aimed more at the wider public than at experts (who might have taken issue with our user-friendly presentation of quite sophisticated art-historical connections).