Comment by xxbondsxx 6 years ago This is awesome! What kind of bias would we expect to see in the training set? 1 comment xxbondsxx Reply cosbynator 6 years ago For example if it consumes lots of data that uses the pronoun "he" for doctor, it's much more likely to spit out "he" in a medical context.Since the model lacks world knowledge for new words, sometimes it also ascribes words to a specific cultural origin / group that is completely wrong.
cosbynator 6 years ago For example if it consumes lots of data that uses the pronoun "he" for doctor, it's much more likely to spit out "he" in a medical context.Since the model lacks world knowledge for new words, sometimes it also ascribes words to a specific cultural origin / group that is completely wrong.
For example if it consumes lots of data that uses the pronoun "he" for doctor, it's much more likely to spit out "he" in a medical context.
Since the model lacks world knowledge for new words, sometimes it also ascribes words to a specific cultural origin / group that is completely wrong.