Before revision:  Specifically, our approach facilitates more explainable biases by allowing us to 1) use the relative effectiveness of inducing biases for different demographics as a new dimension for bias evaluation, and 2) discover topics that correspond to demographic inequalities in generated text. Furthermore, our mitigation experimentsexemplify our technique 's effectiveness at equalizing the amount of biases across demographics while simultaneously generating less negatively biased text overall.
After revision:  Specifically, our approach facilitates more explainable biases by allowing us to 1) use the relative effectiveness of inducing biases for different demographics . The second scenario is useful for mitigating biases in downstream applications such as dialogue generation. In our experiments, the mitigation technique proves to be effective at equalizing the amount of biases across demographics while simultaneously generating less negatively biased text overall.