I propose the Monte Carlo hiring process: heads means the applicant is hired without question, otherwise they get to go through the regular interview routine.

I like it. Exploration vs exploitation is used in a lot of optimization algorithms (and in reinforcement learning) meaning that there's a low probability that the agent just decides to make a random choice instead of making a greedy choice.

That would ensure also diversity of staff. Very good idea.

Why do you think that? Isn't it rather sexist/racist to argue this?

The candidate stream is itself not "diverse" (assuming you are using the normal meaning of the word of lots of women+racial minorities). Simply randomly making offers wouldn't alter the outcomes because those people aren't being de-selected by skills testing to begin with - unless you believe the 'diverse' candidates are less skilled programmers.

It's not totally obvious to me that random hiring would be worse. Most people can do most jobs, given the right experience and opportunity.

>It's not totally obvious to me that random hiring would be worse

Does this have some implied conditions I'm missing? Because to me it seems absolutely obvious that filtering for people who have experience/a degree will vastly improve your outcome over true random hiring.

A lot of things seem obvious but aren't actually true. Plenty of people with degree and experience coasted on nothing, or have personalities so abrasive as to make working with them all but impossible. Disappointingly I have poor experience with degrees actually instilling any sense of diligence, or even research capabilities, thus making them questionable even when recruiting for fields such as R&D, where it should be truly an obvious choice. At least a retrained nurse has some basic curiosity and a critical eye, though it's a bit of a shame, what with the nursing staff shortage.

And, also personally, I've had great experience with people who migrated from absolutely unrelated fields (e.g. several people who retrained - within same company - from support into software development). Similarly I had great experience with fresh interns turning out to be brilliant theory people.

Right. It logically follows that random applying would be a good strategy: selecting randomly from top-paying jobs, you would reply to job offers for e.g. software engineer, brain surgeon, architect or hedge fund manager, to increase the chances of being randomly hired.

That is effectively how I got my last 2 jobs in software engineering. Picking a few keywords and spamming out your resume seems the only way to match the equivalent efforts from recruiters.

>That is effectively how I got my last 2 jobs in software engineering

Are you saying that you had no qualifications at all before? Because that's what they're saying, just applying for any high-paying job, even if you don't have the requirements.

I mean my anecdata to serve as a realistic example of the hyperbolic concept of just wildly applying anywhere at random.

In both cases, I was switching industries (from ASIC design to IoT cloud software to data analytics). So, I arguably had some qualifications and arguably none at all.

Can you tell how fast did you acclimate and how did your employer look at this?

> This is obviously not the case.

Isn't it? While machine intervention might be able to weed out the most obvious low-quality candidates, I don't think there's any strong evidence that most hiring processes actually select the strongest hires - just that they, out of the set of candidates that progress to the point of human intervention (i.e. interview), select a decent one.

The problem is that interviews don't scale well, and some kind of automatic culling of the field of candidates is necessary. Engineers, managers, etc all want to feel that whatever machine solution (keyword searching in resumes, applying AI to recorded video statements, HackerRanks) they select is better than random - but there's no incentive for them to check that that's true.

Obviously randomness + interviews is better than pure randomness, but ultimately hiring processes are still pretty random. If you need to weed out most of your candidates, you can't do much better than throwing most of their applications away - and companies end up doing just that, only they cargo cult an "automated process" that claims to do better.

I would say that a random selection process would be worse than most hiring funnels that I've seen. This is doubly true considering the abject terrible quality of the lowest decile of candidate in software engineering. (The "spray and pray" resume machine-gunners would be way over-selected by any hiring process that relies on randomness when the rest of the industry is trying to select by interviewing.)

Has random hiring often been tried? I've never heard of anyone doing it. Not sure random hiring would be optimal, but it would be interesting if there were some data, doubtful it exists, though.

A couple places have tried open hiring (first come, first served) for some low-skilled positions, but with good initial results

https://www.fastcompany.com/90462746/the-body-shop-will-star...