FERET Dataset, 1993, 1996, National Institute of Standards, Dataset funded by the United States military’s Counterdrug Technology Program for use in facial recognition research.
Training Humans is a new landmark exhibition conceived byKate Crawford, AI researcher, artist and professor, and Trevor Paglen, artist and researcher commissioned by Fondazione Prada for its Osservatorio venue.
The exhibition will take place at Fondazione’s Osservatorio venue, located at the 5th floor of the Galleria Vittorio Emanuele II, from 12 September 2019 to 24 February 2020. The press preview will take place on 11 September.
FERET Dataset, 1993, 1996, National Institute of Standards, Dataset funded by the United States military’s Counterdrug Technology Program for use in facial recognition research.FERET Dataset, 1993, 1996, National Institute of Standards, Dataset funded by the United States military’s Counterdrug Technology Program for use in facial recognition research.
When we first started conceptualizing this exhibition over two years ago, we wanted 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. Rather, we wanted to engage with the materiality of AI, and to take those everyday images seriously as a part of a rapidly evolving machinic visual culture. That required us to open up the black boxes and look at how these engines of seeing currently operate. – from the artists
FERET Dataset, 1993, 1996, National Institute of Standards, Dataset funded by the United States military’s Counterdrug Technology Program for use in facial recognition research.CAISA Gate and Cumulative Foot Pressure, 2001, Shuai Zheng, Kaigi Huang, Tieniu Tan and Dacheng Tao Created at the Center for Biometrics and Security Research at the Chinese Academy of Sciences, the dataset is designed for research into recognizing people by the signature of their gait.
Training Humans is the first major photography exhibition devoted to training images: the collections of photos used to train artificial intelligence (AI) systems in how to “see” and categorize the world. In this exhibition, Crawford and Paglen reveal the evolution of training image sets from the 1960s to today.
CAISA Gate and Cumulative Foot Pressure, 2001, Shuai Zheng, Kaigi Huang, Tieniu Tan and Dacheng Tao Created at the Center for Biometrics and Security Research at the Chinese Academy of Sciences, the dataset is designed for research into recognizing people by the signature of their gait.UTK Face, 2017, Zhifei Zhang, Yang Song, and Hairong Qi, Researchers at the University of Tennessee, Knoxville created this dataset of 20,000 faces to classify people by race, gender, and age. According to the dataset, gender is binary and race can be represented by the categories White, Black, Asian, Indian, and Others.
The exhibition explores two fundamental issues in particular: how humans are represented, interpreted and codified through training datasets, and how technological systems harvest, label and use this material.
SDUMLA, HMT, 2011, Yilong Yin, Lili Liu, and Xiwei Sun, The finger and iris prints come from a larger multimodal dataset de veloped at Shandong University in Jinan, China which includes faces, irises, finger veins, and fingerprints for use in biometric applications.SDUMLA, HMT, 2011, Yilong Yin, Lili Liu, and Xiwei Sun, The finger and iris prints come from a larger multimodal dataset de veloped at Shandong University in Jinan, China which includes faces, irises, finger veins, and fingerprints for use in biometric applications.
