What is gained from allowing such bias?
Consequence: men are now more likely shown mechanics job.
What is gained: more accurate content, more interesting content, more engagement.
As a result: men are more likely to be shown jobs interesting for men, and women are more likely to be shown jobs interesting for women.
Which means: Increased chances to find a matching job, and to save time doing so.
We already been through this. It's not ancient history
https://www.tutorialspoint.com/machine_learning/machine_lear...
This is exploration vs exploitation dilemma. For example let's say that 10% of ads are thrown randomly, and from these random rolls these patterns are discovered:
> [Denver+<40-50> years+men]: mechanics +10%
> [Denver+<40-50> years+men]: nurse -5%
Then the system can apply these coefficients on 90% of the other traffic.
If you are making 100% exploration (so 100% random), then it means the people are going to miss their relevant job opportunity (having a net negative impact on the society).
Increasing exploration is a solution that would legally actually reduce biases of previouses patterns, but at the cost of less relevant content.
In all cases, if the bias is real, exploration discovers them and the coefficients already naturally adjust.
One exception, advertisers can artificially restrict saying "I want only men between 30-40" in their targeting filters.
Then what Meta can do ? Not much.
> Then what Meta can do ? Not much.
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“We do not allow advertisers to target these ads based on gender,” Settle said in a 2023 statement.
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Meta can start by doing what they claim they are doing?
What it suggested was people to actually learn something about the world around them. Because we literally have jobs that at one point started as diverse/female dominated and then marketed exclusively at males. For example, IT/programming.
Also, a lot of "traditional" roles don't need additional algorithmic biases to stay the same.
> Nope. What you eventually get is women not getting a variety of jobs they could apply to and a death of men in professions that actually need more men (e.g. nurses, teachers etc.)
"What you eventually get" suggests that using algorithms leads to gender discrepancies. I'm saying gender discrepancies existed long prior to the algorithms. I'm not saying gender discrepancies are good (although I do think they are inevitable), I'm just saying they are the cause, rather than the effect, of the algorithm.
Why do we want to perpetuate biases without a chance to allow it to potentially be corrected?
Second, some "institute" shouldn't be telling a company or anyone really what it can or can't show on its website. The Internet should remain a free place. If you don't like Facebook, don't use it.
Or did I miss obvious sarcasm?
If you get recommendations for "Technology" and someone of the opposite sex doesn't its completely discriminatory.
If you don't think its a problem then you likely dont understand how recommendation systems work.
The only way recommendations could work is you would explicitly state preferences for everything upfront and no engagement data is used.
You've written twice in this thread that you'd need to ban any kind of content recommendation system. Is that what you're advocating for? Your comments read to me as the opposite - you're saying that the only way to 100% solve this issue is by banning any recommendation system, so we shouldn't do anything instead.
This is, of course, not how we treat almost any facet of our society. No law covers 100% of cases, yet we're fine implementing new laws if they improve the situation. Why can't we do the same here?
Are those not goals of yours?
Oh no!
> The ability of job seekers to find jobs they're willing to apply to will go down.
The playing field will be level.
Who doesn't love a perfectly informed market?