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AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights

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141–150 of 190 posts

Re: AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights

#141

Post by ai_slop_hater »

andsoitis wrote: post #98
leonidasv wrote: post #74

Earlier quoted context omitted.

Same thing happened to my wife as well. I helped her tailor her LinkedIn profile and resume with a lot of attention to detail: adding metrics, keywords, results, etc. Nevertheless, she never received any outreach recruiters and got very few application responses. It went like that for months, almost a year. Then she asked ChatGPT 5.x for help. I was skeptical about the changes it recommended (and was skeptical at all…

> I helped her tailor her LinkedIn profile and resume with a lot of attention to detail: adding metrics, keywords, results, etc. FWIW, when I see a resume with metrics and keywords, I immediately filter it out.

Gigachad. Just don’t forget to signal somehow that you aren’t like everyone else, so that legitimate candidates can send their real resume instead of AI generated one.

Re: AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights

#142

Post by jwolfe »

schrodinger wrote: post #133
andsoitis wrote: post #98

Earlier quoted context omitted.

> I helped her tailor her LinkedIn profile and resume with a lot of attention to detail: adding metrics, keywords, results, etc. FWIW, when I see a resume with metrics and keywords, I immediately filter it out.

Same. If it's something like "Refactored the apartment list service improving P99 Latency from 2s to 180ms", it definitely boosts the resumé in my mind. A good engineer would be measuring their impact and likely have numbers like that off the top of their head. But if it's like "Increased revenue by $18.7M by reducing time-to-first-interaction latency from 2.3s to 117ms, increasing conversion by 47% and LTV by 28%,"…

> If it's something like "Refactored the apartment list service improving P99 Latency from 2s to 180ms", it definitely boosts the resumé in my mind. A good engineer would be measuring their impact and likely have numbers like that off the top of their head.

> But if it's like "Increased revenue by $18.7M by reducing time-to-first-interaction latency from 2.3s to 117ms, increasing conversion by 47% and LTV by 28%," with the same fidelity on each bullet, I'm very skeptical.

Do you mind explaining why? The former doesn't indicate caring about business impact whatsoever (is this service in the critical path of any online process? Who knows!) while the latter does.

Re: AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights

#143

Post by Melatonic »

andsoitis wrote: post #121
Izkata wrote: post #117

Earlier quoted context omitted.

> those keyword lists often include, in my experience, proficiency in specific tool use This used to be called "buzzword bingo" and was pretty much required. It was how you got past the initial automated filtering step before a human even saw your resume.

I don’t know whether it was ever effective strategy for candidates, but I will simply say that as a hiring manager for over 12 years, I have never been interested in anyone’s resume when I see that.

Most HR departments have been filtering resumes (or LinkedIn) based on things like keywords for years before they got to you. So your reaction to resumes that heavily use those may be reactionary to being presented with tons of those (by whoever filtered them before you)

Re: AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights

#144

Post by rustystump »

Izkata wrote: post #117
andsoitis wrote: post #106

Earlier quoted context omitted.

Yeah I don’t know what others are doing, but I work in the valley and those elements signal checklist mentality. To wit, those keyword lists often include, in my experience, proficiency in specific tool use, rather than communicating skills that transcend tools, which tells me the person is likely not very dynamic or creative.

> those keyword lists often include, in my experience, proficiency in specific tool use This used to be called "buzzword bingo" and was pretty much required. It was how you got past the initial automated filtering step before a human even saw your resume.

No used to be. It still is standard. Large companies that do not use external recruiters still use keywords and skills matching to find candidates and it drives me nuts.

Re: AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights

#145

Post by mcv »

Timely topic for me. My CV had grown to 7 pages, and I kept reading everywhere that it should be no more than 2, so I asked Gemini to rewrite it. Took a lot of time, because Gemini loves to exaggerate everything, but I'm quite happy with the result.

The first couple of recruiters I sent it to preferred my old 7 page CV. I guess they're not using enough AI yet.

Re: AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights

#146

Post by Melatonic »

andsoitis wrote: post #125
tkiolp4 wrote: post #111

Earlier quoted context omitted.

Metrics: I increased retention 2x; I reduced latency from X ms to Y ms; increased slo to 99.999… those are all meaningless. It was in fashion to put such numbers in cvs maybe 5-10 years ago. Not anymore

They were always lies because they’re imprecise. “I” didn’t do any of those things, you did other things together with other people leveraging company infrastructure to accomplish those things. Tell me about the SKILLS you excel in tha make those things happen.

Why would you not want to know a general idea of what specific technology someone is familiar with ? Someone could be an "infrastructure engineer" and be more proficient in specific tools vs others - don't you want to match that to the job your hiring for ?

Re: AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights

#147

Post by cyberax »

normie3000 wrote: post #118
zdragnar wrote: post #89

Earlier quoted context omitted.

It's not uncommon to get hundreds or thousands of applications per opening for web tech, if the position is advertised on LinkedIn or a similar job board. They'd need to use some automation, even if it is just picking ten at random.

Maybe? I've filtered 300-400 CVs by hand before, and didn't find it particularly time consuming to bin the ones which clearly didn't meet requirements or have any redeeming features. And hiring was not my full-time role.

The last time I posted on HN in the 1-st of the month hiring post, I got around 2 thousand resumes. Pretty much all of them were this kind of: "Increased the performance of the service by 23.123213%" collection of bullet points.

PS: I replied to most of them, I think, but I'm sorry if I missed somebody :(

Re: AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights

#148

Post by anthuswilliams »

normie3000 wrote: post #118
zdragnar wrote: post #89

Earlier quoted context omitted.

It's not uncommon to get hundreds or thousands of applications per opening for web tech, if the position is advertised on LinkedIn or a similar job board. They'd need to use some automation, even if it is just picking ten at random.

Maybe? I've filtered 300-400 CVs by hand before, and didn't find it particularly time consuming to bin the ones which clearly didn't meet requirements or have any redeeming features. And hiring was not my full-time role.

At 90 seconds per resume, that would take up a full 8 hour day. Having gone through this myself, I don't think it's possible to do this much faster than that, even if you have an ATS that optimizes for that workflow.

I often found myself falling into patterns of poor judgement, e.g. mentally filtering out resumes based on the layout because, to my tired and bored mind, they looked similar to the resumes I had seen from unqualified candidates. I actually think some automation is helpful in evaluating them more rigorously.

Re: AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights

#149

Post by cyberax »

rogermarley wrote: post #41

I think resumes will eventually (or have already) become obsolete in tech. The SNR is so low, they offer very thin filtering value. Even taking the tiny bits of the resume that are "hard signal", like GPA, certifications, prior roles, etc, it doesn't translate into their performance in the initial screening interview. This is why what I think the industry sorely needs is examination consortia. Rather than trying to g…

It's hard to design tests for CS. Leetcode is too simplistic, it just tests the basic algorithmic knowledge that is nearly useless for regular software development.

Re: AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights

#150

Post by mcv »

andsoitis wrote: post #125
tkiolp4 wrote: post #111

Earlier quoted context omitted.

Metrics: I increased retention 2x; I reduced latency from X ms to Y ms; increased slo to 99.999… those are all meaningless. It was in fashion to put such numbers in cvs maybe 5-10 years ago. Not anymore

They were always lies because they’re imprecise. “I” didn’t do any of those things, you did other things together with other people leveraging company infrastructure to accomplish those things. Tell me about the SKILLS you excel in tha make those things happen.

In my case it's not a lie: I reduced the time for a complex import process from 1 hour to 3 minutes, a 20 fold improvement. I included it in my CV, but now I wonder if I should take it out.
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