131–140 of 177 posts
Earlier quoted context omitted.
They also say that if they do the analysis globally the effect goes away. Curious, does that not imply that if one domain is biased against some group there would be another where the bias was in its favor?
Also has issues of random chance causing these differences. How many different positions are there that have the chance of a 80% effect?
I think this partially buries the lede: "As a single hiring vendor comes to dominate screening for an industry, it may be more likely that candidates are shut out." If we move to using just a small number of AI models to help do things like hiring, we will amplify biases and possibly completely lock out portions of the population. We need to be very careful when using AI systems to evaluate people in general -- not b…
You might be able to avoid it with a panel of AI, similar to how we try to avoid it by using panels of humans, but even that turns out to be contentious and not surefire.
I have feeling with AI it'll be even worse, since folks / companies can pass the buck (similar to how health insurance companies are now using it to deny folks).
Earlier quoted context omitted.
My fear is that pressing "no" on stuff like that is going to become an auto-rejection in the vast majority of cases
It's probably not going to be an auto-rejection, it's just going to sit in a queue that looks like this Screened Applications [13] Unscreened Applications [39148]
My point is that this is effectively an auto rejection
Earlier quoted context omitted.
>What could justify it? The assumption that applicants from all races are on average equally qualified for every position. Whole subfields of modern academia are based on that assumption.
The assumption is that no one has the authority to decide that all races aren't equally qualified for every position.
I think this partially buries the lede: "As a single hiring vendor comes to dominate screening for an industry, it may be more likely that candidates are shut out." If we move to using just a small number of AI models to help do things like hiring, we will amplify biases and possibly completely lock out portions of the population. We need to be very careful when using AI systems to evaluate people in general -- not b…
> We find that people who submit multiple applications to positions screened by the same algorithmic hiring vendor are more likely to be rejected from every position to which they apply than would be true if the companies made decisions statistically independently from one another. Ten percent of applicants who submit four applications are rejected from all the places to which they apply. > Our research also found th…
A inferior candidate (by skill) is going to be consistently rejected, no?
I think this partially buries the lede: "As a single hiring vendor comes to dominate screening for an industry, it may be more likely that candidates are shut out." If we move to using just a small number of AI models to help do things like hiring, we will amplify biases and possibly completely lock out portions of the population. We need to be very careful when using AI systems to evaluate people in general -- not b…
If you want to make meaningful change in this avenue you really can't use words like "bias" or "systemic" because anywhere from 49-51% of the population will immediately shut down upon hearing that. Someone can argue (and many do to varying levels of success) that systemic bias doesn't exist, which means this doesn't exist, which means there no problem. However, "this AI model can decide that some subset of people, p…
For example, the article here shows disparate impact: that different percentages of applications are passed through the AI filter. But it doesn’t show differential treatment of otherwise identical applications based on race.
I'm struggling to figure out what they're trying to say here in the linked (and very anemic) paper: > 30% of Black applicants apply to at least one position that demonstrates adverse impact against Black applicants. The whole thing reads like a tautology.
You are reading a paper without understanding the language of the paper. Adverse Impact has a specific meaning, and in this case it's specifically meaning that Black candidates were selected only four fifths as often as white candidates when their qualifications were identical. The study is only suggesting that further investigation is warranted.
Earlier quoted context omitted.
>What could justify it? The assumption that applicants from all races are on average equally qualified for every position. Whole subfields of modern academia are based on that assumption.
Unless you believe that Black people are racially inferior, I think this is simply evidence of racial discrimination at a systemic level, from education through employment. AI merely reenforces the systems built to favor white people.
Anyone who’s done hiring wouldn’t be shocked by this: We find applicants are more likely to be rejected from every position they apply to than would be predicted by the baseline of each position making statistically independent decisions. Obviously a rejected resume is more likely to be rejected by every other employer and an accepted resume is more likely to be accepted by every other employer. Like online dating, m…
> Obviously a rejected resume is more likely to be rejected by every other employer and an accepted resume is more likely to be accepted by every other employer. But that wasn't the case for non-algorithmic screening. From the paper: "By contrast, we find that when first round screening is not mediated by a single screening procedure, systemic rejections are close to the baseline. To support the empirical validity of…