> So if a demographic group is more likely to apply to some jobs they are not qualified for, this paper would say they are being discriminated against.
Your understanding appears to be incorrect.
> Our research also found that this pattern does not appear to be the case in other circumstances. We analyzed data from the largest prior study of hiring decisions, which sent 83,000 applications to 108 Fortune 500 firms during the same time period as our study and did not focus on whether AI was used to make decisions. We found that the rate at which applicants were rejected from every firm they applied to in this data was no higher than what you’d expect if each company decided independently of the others.
If it were what you were asserting, then this behavior and results would persist even without AI being used. Instead when they remove the filter for AI decisions (and AI mono-culture in decisions) the effect is no longer present.
This seems to strongly support they argument that effectively a single AI makes a single decision for a candidate across "all" positions they apply for rather than independently assessing them for each position.
Essentially it's more or less saying they're is one hiring manager for the entire industry and if they have a random reason they don't like you, you won't be hired for any job in the industry.
There is a single evaluation function for the industry and if it puts you a negative for any reason in the model's distribution, every job that uses it will do so.
Those are somewhat separate concerns. You could have companies making independent hiring decisions while systematically discriminating against demographic groups, and you could also have companies all use the same system that systematically disadvantages certain individuals, but it's unrelated to their demographics and instead based on things like their resume not being easy to OCR.
In this case, the claim is that both are happening: companies aren't making decisions independently and they're doing so in a way that discriminates against certain demographics. But the evidence needed for each half of the claim is different.
> If it were what you were asserting, then this behavior and results would persist even without AI being used. Instead when they remove the filter for AI decisions (and AI mono-culture in decisions) the effect is no longer present.
> Our research also found that this pattern does not appear to be the case in other circumstances. We analyzed data from the largest prior study of hiring decisions, which sent 83,000 applications to 108 Fortune 500 firms during the same time period as our study and did not focus on whether AI was used to make decisions. We found that the rate at which applicants were rejected from every firm they applied to in this data was no higher than what you’d expect if each company decided independently of the others.
> If it were what you were asserting, then this behavior and results would persist even without AI being used. Instead when they remove the filter for AI decisions (and AI mono-culture in decisions) the effect is no longer present.
Thanks for this note, I missed this when skimming it. I would love to see their actual analysis here explained more than a single line, but this doesn't say the original study found no adverse impact at the job type level (they seem to say this wasn't analyzed), but rather that firms seemed to look more independent. Which makes sense for the headline, but is not about their notes on harms, which I still think have all the weaknesses I outlined.
An AI generated article about single ai run test which in theory had many components and the AI judge declared deepseek "won"?
How many runs were there on each test to account for some temperature variance? Only one.
Did deepseek write better code? Did GPT's code have bugs when doing the regex? The AI "news" article doesn't actually say that. It says that grok thought that GPT's approach could have bugs so it declared deep seek the winner.
This is absolute worthless methodology. And barely measurable methodology - nothing more than a prompt. No definition of what the scoring approach actually is. No definition of what "precision" actually means in this context. This is absolutely worthless and has no business being in the site, forget about on the front page.
So why is it's on the front page? Because it aligns with the current "feels" of the community that deepseek will get better and it shows "bad things" about the en vogue to dislike closed models.
I happen to agree with both of the views, but this site is utterly worthless.
If you want HN to be astro-turfed to the max, just up vote content like this without any critical reading of the.
I mean the past 6 months of "here is my chat gpt blog post of how to use a coding agent" are 1000x better than this "news article".
Seriously the amount of respect I've lost recently for the HN community is incredible. A bit harsh, but very true.
Maybe it's generational thing, maybe it's due to the state of politics, maybe it's a side effect of me getting older, but recently online has turned into nothing but people explicitly (or implicitly) writing about their "team". Comments on this post are nothing but people who clearly see themselves as being on "team deepseek" or "team open models" or some similar variant writing posts in support even though this is probably one of the worst "articles" to make it to the front page on ages.
It clearly doesn't matter. It supports something on their "team" so they support it via comments.
If kills any form of intellectual discussion. It's all just "this is my team".
Have you even used deepseek pro/flash? Yes, it is astroturfed to the maxx. There is a reason for that. The performance/price ratio beats anything available today.
You misused the term 'astroturfed.' If the performance/price is that good than it'll be spreaded by word of mouth and no need to astroturfed to the death.
... and I believe which is happening. I've been advocating for DeepSeek V4 Pro and no one paid me. It's almost too good to be true.
"Don't you understand? I'm on team deepseek! It doesn't matter what's written about it. Heck it doesn't even matter if it's all lies - it supports my team and here's why I love my team."
"You're on the team against me so I oppose everything you say".
Again it's the same problem - what you're doing. I'm not on "team OpenAI". I'm also not on "team deepseek". I'm commenting on how so much of the population is literally unable to see the world unless it is filtered through some "team" lens that they are for or against.
Judge the material based on what's in the material. Not as it boosting or hurting your "team".
The material in this article is crap judge it as crap and say so regardless of your team.
But here you look at my saying something negative about a post that is pro "team deepseek" so the only conclusion you're able to make is that I must be for the other team.
It's the inability to think critically that is astounding me here. So many opinion's people have now is now just "is it for team or against my team". They are unable to even think of anything else.
I wrote that entire post and you even said you couldn't understand it unless you put it through a lens of being for or against a team...
> Your area again making the same mistake as before.
> You are making the most passionate defense of team openai
At no point did I mention Openai, referr to openai or imply anything about openai (just mentioned your reference). Nothing I'm saying weighs in on any form of discussion or debate between Deepseek & Open Models vs OpenAI.
The fact that you are unable to separate those two is your failing, not mine. Your argument is the equivalent of the following:
A: Deepseek ran into a burning building last week and saved 10,000 orphans from a fire.
Me: No Deepseek did not save 10,000 orphans from a burning building last week. Regardless of what you think of Deepseek it didn't save 10,000 orphans. It's an LLM in a computer, not a humanoid robot - if you look at that for 2 seconds you see that claim is nonsense.
You: By attacking those supporting Deekseek you have declared yourself for team OpenAI and are clearly an OpenAI supporter!
Me: Saying deepseek didn't save 10k orphans has nothing to do with OpenAI. It is a lie saying that deepseek saved 10k lives. It's an LLM chat bot. Regardless of how anyone feels about deepseek - discuss it on it's merits not on bs.
You: See! You keep defending OpenAI you open AI shill! Stop passionately defending OpenAI!
So "unlimited" for you is literally one week more than 5 weeks tech companies cap at?
Why not take 10 weeks or 12 weeks? If it's unlimited?
And how many other employees are only taking half of what they would be taking because they feel silently pressured to - and do all of those missing weeks make up for the single extra week you're taking?
Yah this was the part that really threw me as well.
"People would be pleased to have a rejection from us. They'd be proud to carry it sounds with them. Lucky them!"
It's funny, I see an article from Yegge and thought "I like that writer, I haven't read any of his stuff in a while, I'll see what he has to say." Then got to the end and see the links to gas town and gas city and remembered it was the same Yegge that while having accurate foresight about orchestration of agents also was a bit off the deep end in gas town.
But the biggest thing I see in this article is it really sounds like "here is the new company I landed at, and rather than make a post about its product, I'm going instead make a post about how terrible the problem it solves really is, and a post on a proposed solution. And the cues what I'll pop up in a few weeks and just coincidentally post about this new company that just happens to solve this problem in the way I've convinced everyone is the right solution."
While I don't have any evidence of this that's the feeling I left with. And if so, then "thought leaders" are a lot more interesting when not "talking their book."
Counter: I failed a rigorous interview at Facebook years ago and the project lead of their mesh internet Aquila was one of my interviewers. I still was pleased to not have the job because I didn’t really want to be marked with being a Facebook employee.
Look, if you want to make people do work samples from an uncomfortable conference room at your office, be my guest. I am pretty confident I speak for the majority of candidates when I say that that my preference would strongly be for the ability to work on this stuff from wherever I want to.
I mean, that doesn't have to be how it works. You can have a both fixed amount of time, and the ability for a candidate to work in whatever environment they want.
Of course, and if you want to do that, I've got no complaints. What we want is to eliminate pressure and scheduling inconvenience. We're also not unhappy to meet people who are not necessarily experts in our problem domain, but capable enough programmers that they can ramp up given a bit of extra time. I don't feel the slightest bit bad creating that affordance, so long as you can meet the rubric if you're an experienced professional in the time we allot.
Man, maybe it's time for me to give the verge a subscription. There the only ones actually doing any journalism here and a bunch of AI blogs skimming off the top.
You'd be shocked at how many people who work on ads really do delude themselves into thinking people find ads "useful".
Their usual justification is in the end somewhere tied to "people click on ads so they must find them useful". And yet somehow always ignores the fact that their platform often does all it can to hide that ads are ads and makes them look as much like content as possible.
If lots of people work for the company, they’re making a lot, and paying a lot, in the world we live in professional ethics in tech are considered quaint and naive, if they’re even on the radar.
Can you imagine wanting to go into advertising? Surely it must be a last resort, or they were tricked into it, like going to work for Facebook or Google to do important bleeding edge work.
The 'advertising' part only makes sense if it seeped in small degrees at a time.
Ads can be useful when they are optimized for users and not for advertiser/ad platform.
I do agree with you about the deluding part though. I was (as a user) all for hyper-personalization of ads on all platforms when I worked in ads. Since I’m not longer working in ads, I’m more skeptical and value privacy a lot more.
Honestly, the core problem is that we can’t trust the platforms selling the ads.
Yeah and private health insurance can be useful if it is designed to pool risk across a population, help make healthcare costs transparent and pay for treatments that people need. But that's not where the money is.
Your understanding appears to be incorrect.
> Our research also found that this pattern does not appear to be the case in other circumstances. We analyzed data from the largest prior study of hiring decisions, which sent 83,000 applications to 108 Fortune 500 firms during the same time period as our study and did not focus on whether AI was used to make decisions. We found that the rate at which applicants were rejected from every firm they applied to in this data was no higher than what you’d expect if each company decided independently of the others.
If it were what you were asserting, then this behavior and results would persist even without AI being used. Instead when they remove the filter for AI decisions (and AI mono-culture in decisions) the effect is no longer present.
This seems to strongly support they argument that effectively a single AI makes a single decision for a candidate across "all" positions they apply for rather than independently assessing them for each position.
Essentially it's more or less saying they're is one hiring manager for the entire industry and if they have a random reason they don't like you, you won't be hired for any job in the industry.
There is a single evaluation function for the industry and if it puts you a negative for any reason in the model's distribution, every job that uses it will do so.
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