by Angela Guess

DJ Pangburn recently wrote in The Creators Project, “People could be forgiven for thinking the building of neural networks and artificial intelligence isn’t labor intensive. That these things are simply the work of creative engineers and computers alone. But as artist Sebastian Schmieg illustrates in his latest work, Segmentation.Network, there is actual human labor behind the artificial intelligence and neural networks. Not just humans dreaming up advanced algorithms, but a labor force tasked with teaching the algorithms how to think and dream.”

He continues, “As Schmieg explains, Segmentation.Network ‘makes visible the hidden and often exploitative manual labor that goes into building neural networks and artificial intelligence’ by playing back over 600,000 segmentations (basically, an image outline) created by crowd workers for Microsoft’s COCO image recognition dataset. The dataset is derived from photos on Flickr and is used in machine learning for training and testing purposes.”

Pangburn goes on, “What Segmentation.Network plays back is a random collage of image segmentations at their original position. Each segmentation consists of multiple coordinates, and the piece shows the manual process of creating these coordinates in fast-forward. To create Segmentation.Network, Schmieg downloaded the whole dataset, extracted the segmentation data, and is now drawing it with Javascript. ‘A segmentation is an exact outline of all objects deemed relevant inside a single image,’ Schmieg tells The Creators Project. ‘Each outline is associated with an object category. Outlines are created manually click by click. Basically, it’s the most detailed understanding of an image and its content that you can produce’.”

Read more and check out the images here.

photo credit: Sebastian Schmieg