'Excavating AI' Re-excavated: Debunking a Fallacious Account of the JAFFE Dataset

Autor:	Lyons, Michael J.
Rok vydání:	2021
Předmět:	Computer Science - Computers and Society Computer Science - Artificial Intelligence Computer Science - Computer Vision and Pattern Recognition Computer Science - Machine Learning 68T01 K.4.0
Druh dokumentu:	Working Paper
Popis:	Twenty-five years ago, my colleagues Miyuki Kamachi and Jiro Gyoba and I designed and photographed JAFFE, a set of facial expression images intended for use in a study of face perception. In 2019, without seeking permission or informing us, Kate Crawford and Trevor Paglen exhibited JAFFE in two widely publicized art shows. In addition, they published a nonfactual account of the images in the essay "Excavating AI: The Politics of Images in Machine Learning Training Sets." The present article recounts the creation of the JAFFE dataset and unravels each of Crawford and Paglen's fallacious statements. I also discuss JAFFE more broadly in connection with research on facial expression, affective computing, and human-computer interaction. Comment: 20 pages, 4 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2107.13998 Zobrazit plný text záznamu View this record from Arxiv