You're wildly mischaracterizing what I said. I didn't suggest "people can't handle my truth". I suggested the article we are discussing says there are certain truths that ML systems should not learn.
The article explicitly recommends building systems which can't learn those things, and suggests characterizing them is a first step:
"We recommend addressing this through the explicit characterization of acceptable behavior. One such approach is seen in the nascent field of fairness in machine learning, which specifies and enforces mathematical formulations of nondiscrimination in decision-making (19, 20). Another approach can be found in modular AI architectures, such as cognitive systems, in which implicit learning of statistical regularities can be compartmentalized and augmented with explicit instruction of rules of appropriate conduct (21, 22)."
According to the article, the most closely related work "is concurrent work by Bolukbasi et al. (6), who propose a method to “debias” word embeddings."
(Recall that in the context of the article, "bias" is something that generates true predictions that are objectionable rather than something which is false.)
The article explicitly recommends building systems which can't learn those things, and suggests characterizing them is a first step:
"We recommend addressing this through the explicit characterization of acceptable behavior. One such approach is seen in the nascent field of fairness in machine learning, which specifies and enforces mathematical formulations of nondiscrimination in decision-making (19, 20). Another approach can be found in modular AI architectures, such as cognitive systems, in which implicit learning of statistical regularities can be compartmentalized and augmented with explicit instruction of rules of appropriate conduct (21, 22)."
According to the article, the most closely related work "is concurrent work by Bolukbasi et al. (6), who propose a method to “debias” word embeddings."
(Recall that in the context of the article, "bias" is something that generates true predictions that are objectionable rather than something which is false.)