Posted by sambellll 17 hours ago
There is another name for it: a waste of electricity.
But wait, not waste! Consumers paid for it fully, with nice profit margins.
You and me, paid.
Try using google flights, or booking.com: the prices shown in search results list are frequently significantly different from those in a single result. It's a nondeterministic compute when it's easy to spot it. But it's not always that easy.
It's all sad, to be honest.
BONUS POINTS: 5.0
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Google Summer of Code (GSoC) participation: +5
Credentialing helps maintain a quality floor. Does this person have basic employable skill? Nothing more. It actually doesn’t help you identify levels of talent and skill which is a universal hiring problem.
We do have a credential - a CS degree. And you can see it is a mixed signal. Employers can choose of their own free will to take risks on employees that do have this credential, or not.
Mandating by law that you must have a CS degree doesn’t seem to help our field as we famously have high performers across the spectrum of formal education.
> Resumes have never been a good predictor of success
Applies broadly to the world, it’s not unique to tech
If you know what you’re looking for, you just start skimming them and maybe ranking them based on your own rubric. If it’s an obvious “no” you can usually tell within 5 seconds skim. Once you have a handful of high ranking ones, stop, and talk to them. Repeat as necessary until you have a short list of people you’d want to hire. There might be 9900/10000 resumes you never even looked at and maybe one of them would have been slightly better but you can’t let perfection be the enemy of progress. Stand by your convictions of feeling the candidate is qualified and capable and meets what you expect and hire them, get back to business.
Having been in “talent shortage” mode for a long while I’d rather have 10000 resumes than 3. Having to pick one from a suboptimal selection is an awful position to be in, but sometimes a necessity.
I don’t think the point of a lot of this is to optimize your resume. It’s to show how arbitrary these systems are.
You read my mind. If the answer is “no”, then we can ignore this.
But I'd also assume that their competitors are doing something similar so I don't think we as an industry can just ignore that it's happening.
That seems to be a different type of product.
I’m surprised open source contributions count for so much. first I thought was “is that something people actually list in as resume?”. But it looks like it pulls your GitHub account and appends that information.
That kind of unfortunate for anyone who doesn’t use GitHub
But logical inference itself is limited. You still have to find out if p is true or not - the ground truth.
How do you find that? You would be able to define in the prompt that if resume has p, infer q and do this. But determining the truth value of p is something LLM cannot do.
It’s not a limitation of the LLM. It’s the limitation of logic itself. You take 10 humans and give them the resumes with the same rubrics as the LLM. You’ll get a similar range of scores because everyone would assign different values.
The issue is not in logical inference. It’s in determining the value of p, which takes much more than logic. And current LLMs are limited to being logical.
In my experience, cold-applying has always worked essentially as a black hole, and LLMs haven't changed that much. The reality is that alternative avenues are always necessary to get the job you want. That could be a third-party recruiter; reaching out to a hiring manager on LinkedIn; or using your network to get referrals. Those continue to work whether the company is using a bone-headed tool like this or not.
It is actually a very hard to solve problem.
Chickens coming home to roost.
> *SCORES MUST NEVER DEPEND ON THE FOLLOWING FACTORS:*
> - College, university, or educational institution name
> - CGPA, GPA, or academic grades
I don't understand why they would omit these factors from the evaluation.
Only hiring MIT graduates sounds great to a lot of tech folks! Automatically rejecting applicants from HBCUs, however, sounds like a lawsuit
As to GPA thing, I think it's just to stop the LLM glomming onto an obvious numerical grade? LLMs like to rank things by obvious dimensions, and whether someone had a 4.0 or a 3.8 in grad school makes very little difference to their performance 10 years down the line.
> But it didn’t. After the company trained the algorithm on 10 years of its own hiring data, the algorithm reportedly became biased against female applicants. The word “women,” like in women’s sports, would cause the algorithm to specifically rank applicants lower. After Amazon engineers attempted to fix that problem, the algorithm still wasn’t up to snuff and the project was ended.
And in another org:
> After an audit of the algorithm, the resume screening company found that the algorithm found two factors to be most indicative of job performance: their name was Jared, and whether they played high school lacrosse. Girouard’s client did not use the tool.
https://www.npr.org/2024/04/11/1243713272/resume-bias-study-...
> Their working paper, published this month and titled "A Discrimination Report Card," found that the typical employer called back the presumably white applicants around 9% more than Black ones. That number rose to roughly 24% for the worst offenders.
It'll discriminate by proxy, basically.
Just kidding, my resumes are sent to /dev/null like everybody else’s.
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1: In fact, I will be controversial and say that self-taught engineers tend to be the strongest in their own particular niche, because they are powered by sheer desire to learn and improve. I am routinely appalled by how many people go on forums to ask how to learn a new thing, completely unable to self-direct their learning. I blame the modern school system.
This system would drop a Harvard top graduate for someone having a year of experience in some outsourcing firm.
I worked for a very large job board for the last six years, it's the one you're thinking of. What we found is that the outcomes of paying attention to what school you went to are almost entirely discriminatory, and not predictors of success.
Really depends on the program. In my undergrad program there were some very smart CS students who got great grades that really struggled with the programming. Smart and capable people can be bad at programming and lack many qualities that make for a good hire.