I think about clouds a lot. They’re really strange things – on one hand, humans have gone to great lengths to characterize different kinds of clouds, creating intricate cloud atlases and taxonomies. On the other hand, when we look at clouds we tend to imagine them taking different shapes – faces, animals, and whatnot. AndContinue reading “Clouds”
Tag Archives: Computer Vision
ImageNet Roulette
ImageNet Roulette was part of a broader project to draw attention to the things that can – and regularly do – go wrong when artificial intelligence models are trained on problematic training data. ImageNet Roulette is trained on the “person” categories from a dataset called ImageNet (developed at Princeton and Stanford Universities in 2009), oneContinue reading “ImageNet Roulette”
Making Faces
Kate Crawford and I were invited by Prada Mode to create an exhibition and cultural program at the iconic Maxim’s restaurant in Paris. We transformed the space into a story about the history of facial analysis and a reminder of the dark histories from which contemporary facial recognition systems emerge. Pages from 19th Century phrenologyContinue reading “Making Faces”
Image Operations
Shot in Berlin’s historic Funkhaus, Image Operations. Op.10 is a video installation that highlights emerging forms of computer vision and machine learning. A string quartet performs Debussy’s String Quartet in G Minor, Op. 10. As the video evolves, the perspective of the view slowly changes from that of a camera, to that of an arrayContinue reading “Image Operations”
From ‘Apple’ to ‘Anomaly’ (Pictures and Labels)
For a 2019 commission in the Barbican’s Curve Gallery in London, I took a close look at the most widely-used “training set” used in AI – ImageNet, a database of over 14 million images organized into more than twenty-thousand categories. The installation was made out of approximately 30,000 individually printed photographs, showing the precarious relationshipsContinue reading “From ‘Apple’ to ‘Anomaly’ (Pictures and Labels)”
They Took the Faces…
Contemporary facial-recognition algorithms were first properly researched in the early 1990s. To conduct that research, computer scientists and software engineers need large collections of faces to experiment with and to use as performance benchmarks. Before the advent of social media, a common source of faces for this research and development came from mugshots of accusedContinue reading “They Took the Faces…”
Training Humans
I conceptualized this exhibition with Kate Crawford to tell a story about the history of images used to ‘recognize’ humans in computer vision and AI systems. We weren’t interested in either the hyped, marketing version of AI nor the tales of dystopian robot futures. We wanted to engage with the materiality of AI, and toContinue reading “Training Humans”
The Trolls
As part of broader efforts to manage cyber bullying and online trolls, AI researchers are attempting to create algorithms that automatically detect what kinds of online content constitute “trolling.” This piece is made from a dataset designed to teach AI algorithms what kinds of language patterns are typical of online trolling. Viewers should be warnedContinue reading “The Trolls”
Hallucinations
One of the most common applications of Artificial Intelligence is to do automatic object-recognition and image-captioning. When you upload an image to Facebook or other social media, powerful Artificial Intelligence algorithms can recognize the identities of people in images, the objects, the products and even the places depicted in those images. AIs are taught howContinue reading “Hallucinations”
Behold these Glorious Times!
This video installation is composed of images from two sources. The photographic images in the video are parts of training libraries used to teach artificial intelligence networks how to recognize objects, faces, gestures, relationships, emotions, and much more. They are images designed to teach machines “how to see.” The second kind of images in thisContinue reading “Behold these Glorious Times!”