The Golden Rule as a Heuristic to Measure the Fairness of Texts Using Machine Learning
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To treat others as one would wish to be treated is a common formulation of the Golden Rule (GR). Yet, despite its prevalence as an axiom throughout history, no digitisation of the moral philosophy exists. In this paper we consider how to digitise it so that it may be used to measure sentences such as: the boy harmed the girl, and categorise them as fair or unfair. A review and reply to criticisms of the GR is made. We share the code for the digitisation of the GR, and test it with a list of sentences. Implementing two approaches, one using the USE, and a second using ALBERT. We find F1 scores of 78.0, 85.0, respectively. A suggestion of how the technology may be implemented to avoid unfair biases in word embeddings is made - given that individuals would typically not wish to be on the receiving end of an unfair act, such as racism, irrespective of whether the corpus being used deems such discrimination as praiseworthy.
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