dissident_right t1_j1w4upw wrote
Reply to comment by BraveNewCurrency in NYC's AI bias law is delayed until April 2023, but when it comes into effect, NYC will be the first jurisdiction mandating an AI bias order in the world, revolutionizing the use of AI tools in recruiting by Background-Net-4715
>Why is that "most likely"? Citation needed.
I can't provide a citation since the program was shut down before it had a chance to prove it's accuracy.
As I said, a simple observation however will demonstrate to you that just because a progressive calls an AI's observation 'problematic' (i.e. the Chicago crime prediction algorithm) that 'problematic' here is clearly not the same as inaccurate.
Again, why would you assume that an AI algorithm couldn't predict employee suitability seeing as how well algorithms predict... basically everything else about out world.
Your are simply trying to avoid a conclusion that you don't want to consider - What if men are naturally better suited to be software engineers?
BraveNewCurrency t1_j1wvngh wrote
>What if men are naturally better suited to be software engineers?
First, ignorant people proposed that exact same line of reasoning, but with firefighters instead of SW Engineers. Go read some history on how that worked out.
Second, did you read that link you sent? It claims nothing of the sort, only that "there are physical/mental differences between men and women". No shit, Sherlock. But just because the "average male is slightly taller than the average female" doesn't mean "all men are tall" nor "women can't be over 7ft tall". By the same token, "men are slightly better at task X on average" doesn't mean there aren't many women who can beat most men at that task.
Third, if we implement what you are proposing, then you are saying we should not evaluate people on "how good they are at the job", but merely on some physical attribute. Can you explain how that leads to "the best person for the job"?
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>a simple observation however will demonstrate to you that just because a progressive calls an AI's observation 'problematic'
Haha, you keep implying that I'm ignorant (should I "do my own research?") because I point out the bias (you never addressed the constant racism by the leading AI companies) but you don't cite any data and recite 100-year-old arguments.
Wait. Are you Jordan Peterson?
dissident_right t1_j1wxp3a wrote
>First, ignorant people proposed that exact same line of reasoning, but with firefighters instead of SW Engineers. Go read some history on how that worked out.
Well... I live in a world in which 99% percent of fire fighters are male, so I am guessing the answer is "All the intelligent people conceded that bigger male muscles/stamina made men better at being firefighters and no-one made a big deal out of a sex disparency in fire fighting"?
I'm gonna assume here that you in some sort of self-generated alternate reality where women are just as capable of being fire fighters as men despite being physically weaker, smaller and lacking in stamina (relative to men)?
>doesn't mean there aren't many women who can beat most men at that task
No, but If I am designed an AI algorithm to select who will be best at 'task X' I wouldn't call the algorithm biased/poorly coded if it overwhelming selected from the group shown to be better suited for task X.
Which is, more or less what happened with the Amazon program. Kinda ironic seeing as they... rely on algorithms heavily in their marketing of products, and I am 100% sure that 'biological sex' is one of the factors those algorithms account for when deciding what products to try and nudge you towards.
>constant racism by the leading AI companies
I haven't 'addressed' it because I think the statement is markedly untrue. Many people call the U of Chicago crime prediction algorithm "racist" for disproportionately 'tagging' Black men as being at risk of being criminals/victims of crimes.
However if that algorithm is consistently accurate how can an intelligent person accuse it of having/being biased?
As I said there plenty of bias involved in AI, but the bias is very rarely on the part of the machines. The real bias comes from the humans who either A) ignore data that doesn't fit their a-prioris, or B) read the data with such a biased eye that they draw conclusions from it that doesn't actually align with what the data is showing. See: your reaction to the Stanford article.
>Are you Jordan Peterson?
No.
BraveNewCurrency t1_j276p82 wrote
>Well... I live in a world in which 99% percent of fire fighters are male
So.. Not this world, because it's more like 20% here. (And would be bigger if females weren't harassed so much.)
>no-one made a big deal out of a sex disparency in fire fighting
Sure, ignore history. You are doomed to repeat it.
> I am designed an AI algorithm to select who will be best at 'task X' I wouldn't call the algorithm biased/poorly coded if it overwhelming selected from the group shown to be better suited for task X.
Good thing nobody asks you, because that is the wrong algorithm. Maybe it's plausible short-cut if you are looking for "the best in the world". But given an arbitrary subset of people, it's not always going to be a male winner. You suck at writing algorithims.
>I haven't 'addressed' it because I think the statement is markedly untrue.
Let's summarize so far, shall we?
- You asked how an AI could be racist. I gave you links. You ignored them.
- You asserted the AI is not biased (without any evidence), and later doubled-down by saying those articles are "untrue" (again.. without any evidence)
- You claimed that 99% of firefighters are male (without evidence)
- You assert that "picking all males for a SW position is fine" (without any evidence, and despite me pointing out that it is literally illegal), then doubled down implying that you personally would preferentially hire only males even though there is no evidence that males have an advantage in SW.
You are blocked.
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