There has always been a lot of talk about whether and how artificial intelligence can start making art. And of course, it can. After all, as is well known, everything can be art! However, there is too little discussion about how a data scientist can help the arts in relation to study and research.
Data science combines multiple fields including artificial intelligence (AI), statistics, data analysis and scientific methods to extract value from data.
Art as data
You are currently seeing more art digitized than ever before, with art available online and libraries giving you access to texts as online and downloadable copies. It has even spawned a number of really amazing collaborations with other popular online areas. For example, many world-famous art galleries have chosen to make their collections available in the game Animal Crossing. This means that players can have virtual money in their virtual home.
By making art available in this way, it becomes data. On the one hand, this can create a lot of new problems for institutions that are traditionally unprepared.
Digital art is based on technology. It’s audio, video, animation, immersive experiences, GIFs, code, hybrid mixes of physical and digital, and more. It requires the existence of technology like hardware, storage drives, software, the Internet, media players, etc. And therein lies the issue. Given the speed of change, it is not an issue of whether the technology fails or becomes obsolete, but when.
There are of course a number of challenges, but also enormous potential. This is because digitizing a work of art as part of good practice means cataloging information along with the art itself. So don’t just scan a portrait and put it online, but also include metadata. This information includes dates like the artist. This allows the art to be stored in an organized way as a digital version of the manual cataloging used previously.
Art and data: A simple look at why this is useful
This metadata allows researchers to edit the art very easily and quickly, which is much more complicated and time-consuming to do manually.
For example, the Metropolitan Museum of Art’s website offers a search function for their collections. This allows you to quickly search for an artist and see the results broken down into a number of filters. This gives an instant insight that would otherwise require a lot of manual sourcing and knowledge.