Recent works find that AI algorithms learn biases from data. Therefore, it is urgent and vital to identify biases in AI algorithms. However, previous bias identification methods overly rely on human experts to conjecture potential biases, which may neglect other underlying biases not realized by humans. Is there an automatic way to assist human experts in finding biases in a broad domain of image classifiers? In this talk, I will introduce solutions.