Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias
Table 1: Total effects (TE) of gender bias in various GPT2 variants evaluated on Winobias (WB), Winogender (WG), and the professions dataset (Prof.).
['Model', 'WB', 'WG', 'Prof.']
Before describing the results from the mediation analysis, we summarize some insights from measurements of the total effect. Random model effects are much smaller, indicating that it is the training that causes gender bias.