Ok, I have to say something. I’ve heard the argument many times that DEI efforts force us to “lower the bar” in order to be able to achieve diversity goals. This is always presented as being objectively logical (“it’s just numbers!”). Here’s why it’s wrong:
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It presumes that there is a single, constant, scalar value of “quality” that we can assign to all candidates, and that the goals of hiring should be to maximize this total “quality”, like some kind of score. This is where the “bar” comes from, ie a threshold on a scalar value.
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However, it’s not possible to assign a single number to someone’s potential contributions, because their value to a company / department is multifaceted and dependent on who’s already there, and is not an intrinsic, constant quantity anyway
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(people’s relevant skills and knowledge fluctuate throughout their lives). It’s known that people tend to have unconscious bias toward those who are like them, which yields homogenous workforces if left unchecked. This is bad, because...
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the “wisdom of crowds” depends on people being able to draw from a broad range of information. In other words, a candidate’s strength depends on them bringing in a relatively new perspective.
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This is especially true for AI, so that we can ensure that future technology benefits everyone, not just a small demographic.
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Hiring shouldn’t be about some kind of competition to see who can “AI the best”, and arguing over what percentage is more qualified. This is meaningless because hiring committees are all hiring for a multifaceted set of different reasons.
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They decided that it was valuable to have new skills, perspectives, and experiences, so the makeup of who’s being hired has started to change. This is good and important, because it signals to newcomers in the field that bringing in new perspectives is valued, ...
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and that their worth in this field is not dependent on them looking like and doing the same things as those who’ve already succeeded.
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To sum up, there is no scalar value of “quality” when hiring. New perspectives are good. To people who think they’ve been offered a job they’re not qualified for because of perceived “positive discrimination”, I say:
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You’ve worked so hard to get here. You bring in something unique and valuable, and the hiring committee saw that. You absolutely belong. We need you.
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“pick the best individual” and “diversity adds value” as two routes to maximise overall performance (if that’s the goal?) are often dogmatic beliefs. Perhaps it’s tricky focusing on the benefits of D to a team instead of the societal benefits of the E and I?
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All agreed. Also: underrepresented ppl often face systematic disadvantages throughout their lives, from their "innate abilities" being questioned in childhood to their papers being rejected more. Such factors cause discrepancies between traditional metrics and true potential.
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IMO it is not really important to argue whether some institution lowers bars to women for diversity. Instead of discussing whether the bar is equal now, let's focus on the long-term social effects, i.e. encourage more women to enter STEM, so that bigger pools of female candidates
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will form for STEM jobs. If the bar is unequal it's totally healthy and temporary (and I don't imply it's unequal now). As the candidate pools become larger the gender gap of bars, and more importantly, of careers, will disappear which is the true goal we should pursue together.
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In brief, if you're hiring for a theory slot, you'll turn away more qualified HCI or ML candidates. You hire to build the best department, not to pick the most "deserving" candidate; once you admit that, most of those "lowering the bar" arguments fall apart.
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1. The "quality" scalar can be seen as a function of time, the problem is to only consider t=0.
2. New perspectives can be good, but not necessarily.
3. Too much diversity entails communication breakdown.
OTOH, I agree that DEI doesn't necessarily lower the bar.
Not when that team is comprised of many of the same type of people who use their synergy to systematically disenfranchise, abuse and exclude talented individuals.
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sounds like this fits with “the myth of the objective” bc the pathway of progress resembles the objective, important/necessary stepping stones to actually reaching the goal are missed and progress stalls by way of deception, resulting in local optima)
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