Reviews: Characterizing Bias in Classifiers using Generative Models

Originality: The task of characterizing biases in face classification systems has recently received increasing attention from researchers. While related work either use computer graphics or real-world data, here, the authors propose to use conditional GANs. Related work is mostly adequately cited, although I would recommend to also take the following related computer graphics approaches into account: - Qiu, Weichao, and Alan Yuille. Quality: The claims made are supported by empirical analyses, although the experimental setting is rather limited, because only two classifiers have been tested. The limitations of GANs in terms of generating realistic images have been pointed out adequately.