AI hiring tools may be filtering out the best job applicants
As firms increasingly rely on artificial intelligence-driven hiring platforms, many highly qualified candidates are finding themselves on the cutting room floor.
This really does not surprise me one bit. But also, nobody using these tools really cares. It reduces the amount of applications they need to review, which is often all they care about. Can’t wait for the inevitable company to pop up which will do the AI equivalent of SEO stacking your resume so you can get a job.
Also, perhaps more importantly, this is just going to undo fifty years of antiracism and antisexism work. The biggest problem with AI is that it’s trained on a bigoted system and when it’s used to gatekeep said system, it just creates additional inequality.
Building off your last point, with AI models, bias can come in ways you might not expect. For example, I once saw a model that was trained with diversity in mind, but then only ever output Asian people with a high bias towards women. It seems to me like diversity is something that is difficult to train into a model since it’d be really difficult not to overfit it on a specific demographic.
It might be interesting to see if a random input into the model could be used to increase the diversity of the model outputs. This doesn’t really help with resume screening tools though (which are probably classifiers), only really generative models.
There isn’t really a good way to even define for diversity.
The bad approach is the corporate token diversity, where every picture has to include a white, a black and an asian person, at least 50% have to be women and one of them has to wear a hijab. That might include many groups, but isn’t really representative.
You could also use the “blind test” approach many tech solutions are using, where you simply leave out any hints to cultural background, but as has been shown, if the underlying data is biased, AIs will find that (for example by devaluing certain zip codes).
And of course there’s the “equal opportunity” approach, where you try to represent the relevant groups in your selection like they are in the underlying population, but that is essentially *-ism by another name.
The key point is “missing the best applicants”. Companies care about good enough, not best, most of the time. There are only a few positions where they truly worry about having actually good people, and they’re often wrong about which ones and how many they should care about.
“Good enough”… is going to be AIs themselves, way cheaper than people. Some of the “actually good”, will also be AIs… just the expensive version. A few people will need to stay there to write “general vision” prompts, oversee the lower level AIs, and press Enter.
The interesting part, is that it will be much easier to 100% control the work output of the AIs, letting businesses make data-driven optimizations (by manager AIs), and become way more competitive.
So you’re telling me a fad that doesn’t work actually… doesn’t work? Say it aint so
Automated resume screening tools have always been harmful, and have been employed for years now in a lot of companies. The issue comes down to how to filter applications in a scalable manner, but this seems paradoxical since those same companies then complain about a lack of qualified candidates after rejecting them all, leading those candidates to then apply elsewhere. If these companies hired less-than-perfect candidates instead of being so trigger happy with their rejections, there’d probably be far fewer applications to review in the first place, making these automated screening tools less necessary.
The bias question is more relevant now that companies are using more complex AIs. I’m glad the article brought it up since it’s difficult to quantify how biased a model is towards some groups and against others, and where in the model that bias comes from.
Artificial Intelligence is a bad word for this technology. Why are we not using the proper name for it? Machine Learning. Its not intelligent, and it might not be for a long time. Feed it crap, and you’ll receive crap.
Its not intelligent, and it might not be for a long time. Feed it crap, and you’ll receive crap.
Sounds like humanity.
Reading this article, these tools look into characteristics like hobbies, while apparently ignoring logic in a written text. Sure, the outcome’s gonna be horrible.
Also, you’re gonna miss unique talents because all it does is to learn typical good candidates. No way you’ll find Jobs!
If I get turned down for a job by an AI tool, that tool probably knew I wouldn’t want to work for a company that uses said tool. And therefor it works as intended…?
I’m so happy I never applied for this kind of mass job hunting. I just didn’t like it. I couldn’t believe it was the right thing to do. Turned out, I don’t regret turning down BS.
The mass application boom is so annoying. Seeing a sankey diagram of someone who applied to hundreds of jobs always bothers me.
The mass application boom is so annoying.
Speaking for the UK, this is a requirement to receive unemployment benefits. You have to prove you’re actively seeking a job for a minimum of 35 hours per week, and you’re not considered to be “looking hard enough” if you’re not applying for every single job that you could realistically travel to, no matter how unsuitable you are for the job. If there’s a hospital 5 minutes walk from your house that are recruiting a surgeon, someone on unemployment would be expected to apply despite having zero suitable qualifications. If they don’t, they get sanctioned, which means they don’t receive enough social security to pay their rent and/or food and/or power.
It’s a result of systematic job training and matching. 10s of thousands of people with similar backgrounds (college / university degrees, formalized through central controls, for example), applying through a few websites.
There’s of course gonna be mass application.
Personally, and I know this is extremely anecdotal, I’ve had great success with spending a lot of effort - about least a week each of precisely tailoring the application to the job offering, the job itself, the organization and the people who will make the hiring decision, as well as preparing for the job interview - on a very small number of applications. Even small details matter, like for example putting an emphasis on hobbies and interests that are relevant to the job and the old-fashioned act of calling key people before sending the application, asking a few well-prepared questions, getting your name written down - this ensures that your application sits on the top of the pile. Every single application of mine directly or indirectly refers to a call with at least one relevant person at the organization.
I only need between two to four applications per job and get an interview practically every time, despite large gaps in my CV. The last time around, I was told I “beat” over 100 applicants with this approach, which included two interviews and two tests (which used the standard set of IQ tests and more or less occupation-relevant questions). I prepared for each test and interview as if it as a university exam, which paid off. The thing is though, I still get frustrated by the small number of rejections (which at least tend to explain why I’m being rejected most of the time, because I developed such a good rapport with the people making the hiring decisions), since I spent so much time and effort on each, but at least I don’t feel like I’m helplessly treading water by aimlessly sending hundreds of applications out.
I hope this doesn’t sound like I’m bragging. I do not have any family connections or network of note, my family isn’t rich, my name is even quite strange, which I’ve read should be a disadvantage, but hasn’t impacted me negatively so far. This slow, systematic approach that anyone could use is just how I’ve always done this, which is why I’m so perplexed by people complaining that they have unsuccessfully sent out hundreds of cookie-cutter applications. Of course you won’t get noticed and glossed over if you’re applicant #235 with a near identical application, an identical CV and using the same approach as the 234 applicants before and who knows how many after you.
I can imagine. Vast majority of applications I receive as a manager has nothing to do with the job. Those are often just copypasta used for dozens of letters.
I am a highly skilled…
Just read the first 5 words and throw it away.
Huh, I guess I’ve just adapted with the enshitification arc. It aways seems pretty clear when the publications are not specialized that the “reviews” are really just generated or copy/paste lists of devices with affiliate links - and are essentially just paid advertising (though paid by vendors and not manufacturers in this case). I will agree that it’s infuriating to have to sift through the ever-growing AI generated content to find something which has novel information.
