Before revision:  We tested nine different models, which employed different architectures and recognition algorithms, including discriminative and generative models, all trained to recognize handwritten digits ( from the MNISTset of digit images ). We synthesized controversial stimuli to maximize the disagreement among the models . Human subjects viewed hundreds of these stimuli  and judged the probability of presence of each digit  in each image.
After revision:  We tested nine different models, which employed different architectures and recognition algorithms, including discriminative and generative models, all trained to recognize handwritten digits ( MNIST) and objects in small natural images (CIFAR-10). For each task, we synthesized controversial stimuli to maximize the disagreement among the models . Human subjects viewed hundreds of these stimuli and judged the probability of presence of each digit in each image.