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Warning: this paper contains content that may be offensive or upsetting.  Language has the power to reinforce stereotypes and project social biasesonto others. At the core of the challenge is that it is rarely what is statedexplicitly, but rather the implied meanings, that frame people's judgmentsabout others. For example, given a statement that "we shouldn't lower ourstandards to hire more women," most listeners will infer the implicatureintended by the speaker -- that "women (candidates) are less qualified." Mostsemantic formalisms, to date, do not capture such pragmatic implications inwhich people express social biases and power differentials in language.  We introduce Social Bias Frames, a new conceptual formalism that aims tomodel the pragmatic frames in which people project social biases andstereotypes onto others. In addition, we introduce the Social Bias InferenceCorpus to support large-scale modelling and evaluation with 150k structuredannotations of social media posts, covering over 34k implications about athousand demographic groups.  We then establish baseline approaches that learn to recover Social BiasFrames from unstructured text. We find that while state-of-the-art neuralmodels are effective at high-level categorization of whether a given statementprojects unwanted social bias (80% F1), they are not effective at spelling outmore detailed explanations in terms of Social Bias Frames. Our study motivatesfuture work that combines structured pragmatic inference with commonsensereasoning on social implications.

Social Bias Frames: Reasoning about Social and Power Implications of Language