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169
[–] 2 pts

Anyone familiar with HR practices probably knows of the decades of studies showing that résumé with Black- and/or female-presenting names at the top get fewer callbacks and interviews than those with white- and/or male-presenting names—even if the rest of the résumé is identical.

(((studies)))

[–] 1 pt

Freakonomics had an experiment where they tested this, trying to discover what the value of a name is. They did not see a difference for male vs female, but they came up w three tiers for callbacks. Top tier, traditional, normal, non-ethnic names were in tier 1 (John, Michael, Catherine, etc.). Tier 2 were overly popular and trendy names at the time of birth, (Evan, Brayden, Jennifer, Heather). The last tier, anything ethnic, weird or old fashioned sounding (Demetrius, Homer, Shaniqua, Esther).

Don’t name your kid something weird, hard to spell or super popular.

[–] 0 pt

AI bots quite often reflect the negative biases that can be inherent in training data.

This is the real issue with AI: it's too truthy.

[–] 0 pt

So.. an 'ai' that is not overly cucked still selects based on data then?