Right. If it’s true that women statistically outperform men (with same application documents), it’d be logical to prefer them just on gender alone. Because they likely turn out to be better.
For most jobs it’s hard to do a hiring process without in-person interviews, or at the very least video calls. So I’m not really sure how one could realistically get rid of biases. But I completely agree that whenever there are too many applications to interview everyone individually, the initial screening of applicants should be completely anonymized and rely only only technologies where biases can at least be understood.
For the final step I’m afraid we’ll have to try to train people to be less prone to biased decision-making. Which I agree is not a very promising path.
You’re welcome. I mean it’s kind of a factual question. Is gender an indicator on its own? If yes, then the rest is just how statistics and probability work… And that’s not really a controversy. Maths in itself works 🥹
I’d also welcome if we were to cut down on unrelated stuff, stereotypes and biases. Just pick what you like to optimize for and then do that. At least if you believe in the free market in that way. Of course it also has an impact on society, people etc and all of that is just complex. And then women and men aren’t really different, but at the same time they are. And statistics is more or less a tool. Highly depends on what you do with it and how you apply it. It’s like that with most tools. (And LLMs in the current form are kind of a shit tool for this if you ask me.)
I’m not sure if you mean the social construct or the sex assigned at birth. Probably the latter as you mentioned “on its own”.
I have a lot of issues with the social construct as it’s basically a nicer word for “stereotype”. It looks like men and women alike suffer because of these stereotypes. The social constructs, the stereotypes, are the basis for bias. To me it seems like gender never is “on its own”. It’s the way we perceive the biological sex and compare it to our expectations.
Sex on the other hand is no indicator on its own, I think.
And I agree statistics is always a problem, that’s why LLMs are problematic in a lot of ways.
I meant both sex and gender. They regularly fail to tell me a lot for my own real life. I like some people and dislike others and it’s easier for me to talk to / work with / collaborate or empathize depending on various circumstances. Personality traits, shared goals… Maybe sharing something or it’s the opposite of that. I believe gender or sex or identity is a bit overrated and so is stereotyped thinking for a lot of applications. Or the need to conform to a stereotype. Dress and identify however you like, make sure to give your children an electronics kit, a plastic excavator and a princess dress… And unless that’s really important for some niche application, don’t feel the urge to look into people’s pants and check what’s in there.
Right. If it’s true that women statistically outperform men (with same application documents), it’d be logical to prefer them just on gender alone. Because they likely turn out to be better.
Thanks for the voice of reason in this sea of hate.
From my pov it would be best to have completely anonymised applications and no involvement of AI in the hiring process.
For most jobs it’s hard to do a hiring process without in-person interviews, or at the very least video calls. So I’m not really sure how one could realistically get rid of biases. But I completely agree that whenever there are too many applications to interview everyone individually, the initial screening of applicants should be completely anonymized and rely only only technologies where biases can at least be understood.
For the final step I’m afraid we’ll have to try to train people to be less prone to biased decision-making. Which I agree is not a very promising path.
You’re welcome. I mean it’s kind of a factual question. Is gender an indicator on its own? If yes, then the rest is just how statistics and probability work… And that’s not really a controversy. Maths in itself works 🥹
I’d also welcome if we were to cut down on unrelated stuff, stereotypes and biases. Just pick what you like to optimize for and then do that. At least if you believe in the free market in that way. Of course it also has an impact on society, people etc and all of that is just complex. And then women and men aren’t really different, but at the same time they are. And statistics is more or less a tool. Highly depends on what you do with it and how you apply it. It’s like that with most tools. (And LLMs in the current form are kind of a shit tool for this if you ask me.)
Is gender an indicator on its own?
I’m not sure if you mean the social construct or the sex assigned at birth. Probably the latter as you mentioned “on its own”.
I have a lot of issues with the social construct as it’s basically a nicer word for “stereotype”. It looks like men and women alike suffer because of these stereotypes. The social constructs, the stereotypes, are the basis for bias. To me it seems like gender never is “on its own”. It’s the way we perceive the biological sex and compare it to our expectations.
Sex on the other hand is no indicator on its own, I think.
And I agree statistics is always a problem, that’s why LLMs are problematic in a lot of ways.
I meant both sex and gender. They regularly fail to tell me a lot for my own real life. I like some people and dislike others and it’s easier for me to talk to / work with / collaborate or empathize depending on various circumstances. Personality traits, shared goals… Maybe sharing something or it’s the opposite of that. I believe gender or sex or identity is a bit overrated and so is stereotyped thinking for a lot of applications. Or the need to conform to a stereotype. Dress and identify however you like, make sure to give your children an electronics kit, a plastic excavator and a princess dress… And unless that’s really important for some niche application, don’t feel the urge to look into people’s pants and check what’s in there.