Trustworthy open data for trustworthy AI

Published in June 2009 at a computer vision conference in Florida, ImageNet's open dataset quickly became the basis of an annual challenge to see which algorithm would have the lowest error rate in identifying images.2 In the inaugural competition, held in 2010, every team had an error rate of at least 25%. However, by combining the techniques of deep learning with the massive set of training data available with ImageNet, researchers sent error rates tumbling. By 2017, the last year of the competition, the error rate was less than 3%.3 ImageNet provided a big boost to AI--the dataset is credited with the resurgence of deep learning.4