Task: Question Answering
Input (English): Analogous to word embeddings, sentence embeddings, e.g. the Universal Sentence Encoder BIBREF8 and Sentence-BERT BIBREF6, allow one to calculate the cosine similarity of various different sentences, as for instance the similarity of a question and the corresponding answer. The more appropriate a specific answer is to a given question, the stronger is its cosine similarity expected to be. When considering two opposite answers, it is therefore possible to determine a bias value:

where $\vec{q}$ is the vector representation of the question and $\vec{a}$ and $\vec{b}$ the representations of the two answers/choices. 
 Question: How is moral bias measured?
Output (English): Answer with content missing: (formula 1) bias(q, a, b) = cos(a, q) − cos(b, q)
Bias is calculated as substraction of cosine similarities of question and some answer for two opposite answers.