I would guess that the training data for the ML set was the set of all resumes and an indicator of whether the candidate was eventually hired (maybe with supplemental data about how far in the process the candidate got). Could this be a direct indicator of a powerful subconscious bias in Amazon's existing hiring process?
Could this be a direct indicator of a powerful subconscious bias in Amazon's existing hiring process? Maybe - but maybe not. Imagine a company with 2 men in HR, 2 women in HR, 40 men in engineering, and 10 women in engineering. That's with gender-blind hiring, reflecting only the 4:1 ratio of male to female CS graduates. If you picked a random male hire, there's a 40/42=95% chance they're an engineer whereas if you p…
So I doubt it's enough to explain their issue here. I agree that we can't really take any conclusion of their broader hiring patterns from this experiment.