“Deep learning” is a branch of artificial intelligence that allows a computer to learn to identify and categorize data without human supervision, a kind of technology commonly used in image recognition, facial detection, computer vision, and natural language processing software, among many other things. This series, titled Shallow Learning, compares the way people see photographs to the way algorithms see photographs.
Two commonplace yet sophisticated digital tools that recognize or “see” photographs were central to this work. Each of the images in this series is a composite that started as a single image from a past project. These leftover images, which had never been published, exhibited, or posted on the internet, were used as search criteria in Google’s “search by image” feature. This function of the search engine is typically used to track down the provenance of an image found online, but because the images I was searching for did not exist online, the search engine instead offered a selection of visually similar images-- algorithmic guesses at what these pictures showed. I then selected one of these “best guesses” from Google, placed it next to the original image on a blank canvas in Photoshop, and filled in the area between the two images using the “content aware fill” function.
I was motivated to do this because I have observed that the digital tools I use in my practice as an artist are beginning to do more of their own thinking. And just as i wonder what I can learn about the world by looking at images, I now also wonder what images are learning about the world by looking at each other.
click here for a virtual tour of When Images Collide at the Wilhelm Hack Museum