>Isn't the whole point of machine algorithms to find the best spot between variance and bias? In which case, every algorithms will have some bias. This referen

>Isn't the whole point of machine algorithms to find the best spot between variance and bias? In which case, every algorithms will have some bias. This references two different, almost opposite, meanings of the word bias. The meaning in TFA is being individually subject to judgements about groups (eg an individual AA prisoner being denied parole because AAs as a population have higher rates of recidivism) whereas in the context of ML it refers to a model ignoring important features of a dataset.