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how would a ML model find applicants with any kind of disability unless it was freely volunteered in a resume/CV?

A few off the top of my head:

(1) Signals gained from ways that a CV is formatted or written (e.g. indicating dyslexia or other neurological variances, especially those comorbid with other physiological disabilities)

(2) If a CV reports short tenure at companies with long breaks in between (e.g. chronic illnesses or flare-ups leading to burnout or medical leave)

(3) There are probably many unintuitive correlates irt interests, roles acquired, skillsets. Consider what experiences, institutions, skillsets and roles are more or less accessible to disabled folk than others.

(4) Most importantly: Disability is associated with lower education and lower economic opportunity, therefore supposed markers of success ("merit") in CVs may only reflect existing societal inequities. *

* This is one of the reasons meritocratic "blind" hiring processes are not as equitable as they might seem; they can reflect + re-entrench the current inequitable distribution of "merit".



>If a CV reports short tenure at companies with long breaks in between (e.g. chronic illnesses or flare-ups leading to burnout or medical leave)

This is a case where it may benefit a candidate to disclose any disabilities leading to such an erratic employment pattern. I don’t proceed with candidates who cannot explain excessively frequent job hops because it signals that they can’t hold a job due to factors I’d want to avoid hiring, like incompetence or a difficult personality. It’s a totally different matter if the candidate justified their erratic employment due to past medical issues that have since been treated.


>medical issues that have since been treated

And what if they haven't been? Disability isn't usually a temporary thing or even necessarily medical in nature (crucial to see disability as a distinct axis from illness!). Hiring with biases against career fluctuations is, I'm afraid to point out, inherently ableist. And it should not be beholden on the individual to map their experienced inequities and difficulties across to every single employer.


I think the point of this guidance is that "hiring AI" is not actually intelligent and will not be able to read and understand a note about disability on a resume. It will just dumbly match date ranges to an ideal profile and throw out resumes that are too far off.


>* This is one of the reasons meritocratic "blind" hiring processes are not as equitable as they might seem; they can reflect + re-entrench the current inequitable distribution of "merit".

they are not meant to be "equitable". they're meant to provide equality of opportunity, not equality of outcome


Oh agreed! Sorry about mixed terminology. Though they don't really provide "equality of opportunity" either :/ People w/ more privelege, at the starting line, will have more supposed 'merit' and therefore the CV-blindness only reflects existing inequalities from wider society. A different approach might be quotas and affirmative action.


I think the poster is arguing that the things we call merit reflects the ability to do the job well. Any system of hiring has to consider the ability to hire the best person for the job. Quotas are an open-admission we can no longer do this. Affirmative action is trickier as some affirmative action can be useful in correcting bias and can actually improve hiring. Too much once again steers us away from the best person for the job.

This is important and tricky as if we have across the board decreases in hiring the best person for the job we end up with a less productive economy. This means our hiring practices directly compete against other aims like solving poverty.




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