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

arxiv.org

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

#101

Post by reillyse »

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.

You must be a pre 5.0 model so.

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

#102

Post by mikeyouse »

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.

Which is a very “HN” sentiment when the vast majority of recruiters and hiring managers are absolutely not doing the same. Especially for roles outside of tech.

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

#103

Post by davebren »

charliebwrites wrote: post #15

Anecdata, sample size of one: When I was looking for my next role after being laid off, I didn’t get much of a response with my human handmade resume despite my experience Just for kicks, I asked ChatGPT to “Analyze my resume and give it a score for what percentage it was in” then I asked it to revise it to make it score as high as possible I still tweaked and fact checked it but after I started sending that out, I g…

Probably gonna get downvoted for this, but when you give an anecdote you don't have to preface it with "anecdata, n=1 sample size".

We know it's from your individual experience because it's a story about your individual experience. We've been doing this for all of human history. This is some kind of strange milieu of trying to always sound scientific, or it's fear of the "well akshually I'm gonna need to see a random placebo controlled trial", which is equally annoying.

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

#104

Post by ivansmf »

I suspect the entire industry uses "auto-raters", where an agent instance is used to scores the agent's output. The idea is similar in intent as using adversarial networks to train image generation, minus the human labelers. Raising the scores of the auto-rater then becomes the metric teams optimize, and it is no wonder the end result is that the agent scores its own generated content the highest.

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

#105

Post by hiAndrewQuinn »

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.

What counts as a keyword here? If you're hiring for a frontend developer and you see e.g. "Redux" do you just can it?

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

#106

Post by andsoitis »

mikeyouse wrote: post #102
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.

Which is a very “HN” sentiment when the vast majority of recruiters and hiring managers are absolutely not doing the same. Especially for roles outside of tech.

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.

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

#107

Post by andsoitis »

hiAndrewQuinn wrote: post #105
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.

What counts as a keyword here? If you're hiring for a frontend developer and you see e.g. "Redux" do you just can it?

Knowing or having experience with Redux isn’t going to cause me to pick you over someone else who doesn’t list it for a job where I’m paying you hundreds of thousands of dollars. I look at other skills.

I would not can it in isolation, but if I see a comma-separated list like: “proficient in redux, react, html, JavaScript, sql, kubernetes, word and excel”… then yes, you don’t make the cut.

Or if you list your Microsoft qualifications or your MIT continuing education courses. These are all negative signals.

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

#108

Post by davebren »

tayo42 wrote: post #86
charliebwrites wrote: post #15

Anecdata, sample size of one: When I was looking for my next role after being laid off, I didn’t get much of a response with my human handmade resume despite my experience Just for kicks, I asked ChatGPT to “Analyze my resume and give it a score for what percentage it was in” then I asked it to revise it to make it score as high as possible I still tweaked and fact checked it but after I started sending that out, I g…

Llms were good for being objective and helping cut out stuff from mine. Harder to do when you personally think everything you ever did is important.

It actually is important and if I was hiring you I'd find it useful to get a more comprehensive understanding of your experience, especially if there's something I'm aware is a very challenging problem to solve. And it would provide more things to cross-examine in interviews to make sure it's not fake. The idea that people hiring are saving time by not reading an extra resume page when deciding on someone that will hopefully work there for years is ridiculous.

For some reason that's the minority opinion because everything has to be dumbed down now.

And how is a resume with the most important or recent work highlighted and at the top worse than a resume with that plus the rest of your experience after it?

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