Algorithmic Monocultures in Hiring

Your understanding appears to be incorrect.

> Our research also found that this pattern does not appear to be the case in other circumstances. We analyzed data from the largest prior study of hiring decisions, which sent 83,000 applications to 108 Fortune 500 firms during the same time period as our study and did not focus on whether AI was used to make decisions. We found that the rate at which applicants were rejected from every firm they applied to in this data was no higher than what you’d expect if each company decided independently of the others.

If it were what you were asserting, then this behavior and results would persist even without AI being used. Instead when they remove the filter for AI decisions (and AI mono-culture in decisions) the effect is no longer present.

This seems to strongly support they argument that effectively a single AI makes a single decision for a candidate across "all" positions they apply for rather than independently assessing them for each position.

Essentially it's more or less saying they're is one hiring manager for the entire industry and if they have a random reason they don't like you, you won't be hired for any job in the industry.

There is a single evaluation function for the industry and if it puts you a negative for any reason in the model's distribution, every job that uses it will do so.

https://www.pnas.org/doi/10.1073/pnas.1702413114

Can you expand on this? How is a whole demographic group not qualified for jobs on wide spectrum? Is this about certain industries? Certain jobs? Certain groups?

1) these tests are valid and objective

2) they are qualified to understand how personalities would interact in a complex system

It's astrology for professionals, and companies have let themselves be captured by what are effectively religious zealots.

https://en.wikipedia.org/wiki/Griggs_v._Duke_Power_Co.

HR rep said those applicants should probably go see a shrink instead (!!???) and that was the end of me interviewing there.

The testing needs to end. The people using these tools don't know how they work, what they are testing and what blanket denials of personality types really means.

I'm also getting maybe 1 INITIAL interview every 3 months right now because of this AI screening stuff and I just haven't felt like re-writing my resume to game them.

(There are some extreme measures that you can try like applying under a different name, although that then forces some awkwardness later on when you actually need your government name for tax and bank information)

> They manage to screen me out before I have the opportunity to talk about anything computing related

When I was in college about 10 years ago, I was dreaming a company would interview me on actual algorithms, but sadly I rarely had the occasion to do anything above basic coding.

If you want to see clearly what you can do to get hired, the following perspective helped me a lot. From experience, most hiring processes seem to be shaped less by technical signal and more by the interviewer's defensibility strategy in case of a bad hire. What I mean by that should be clearer from the list below:

- informal interview plus experience matching, hires based on how similar candidate prior jobs seem to be for current role <- if candidate is bad, the interviewer can justify the decision by pointing to the candidate's background.

- informal interview and vibe check with the team or personality test check if candidate is compliant if senior or charismatic if junior <- if the hire is bad, responsibility is diffused across the group.

- take-home project with a nominal 1-hour time limit, but an implicit expectation that candidates spend days on it. Since the interviewer cannot verify how long anyone spent, they default to rewarding the most polished submission.

- take-home project with narrow stated requirements, followed by judgment against unstated "best practices" the company follows <- if the hire is bad, the interviewer can point to the candidate's code and show it matched already what the company looked for, since the style is recognisable.

- CV farm, the company is collecting CVs and has no serious intent to hire <- interviewer doesn't exist

- if the interviewer has no skin in the game (is not verified, performance doesn't matter, they're a consultant leaving next month anyway), anything could happen. This is the most dangerous kind of interview because almost anything can happen and it gives you the least actionable data.

- formal interview pipeline, usually found at large corporations or in finance; interviewer has a clearly scoped job and are expected to evaluate one part of the candidate against a rubric, not make a general judgment about overall hireability. Biases will still exist, but they are more constrained because the process uses multiple interviewers, trained evaluators, explicit scoring grids <- if the hire is bad, the decision is defensible because the interviewer followed the assigned process.

So, interview pipelines can be predictable. It is that you should identify what kind of process you are in as early as possible. If it is experience matching, make your background look obviously adjacent to the role. If it is a take-home, assume polish will count more than the stated time limit. If it is a vibe screen, technical skill may not be the primary variable. If it is a formal pipeline, prepare for the rubric. And if it is a CV farm or a low-accountability interview, do not over-update on the rejection.

In your specific case, I wouldn't overindex on on the intelligence or personality assignment. More probable the CV already got deproritised, but they also sent you the test automatically. The rejection may tell you less about your ability than about the kind of pipeline you were in.

Learn to play a cheap instrument, garden vegetables, paint miniatures, volunteer at pet shelters, or travel to odd destinations. Play the long game, and remember to have fun.

You owe corporate nothing outside what they paid for... and not a cent more. =3

https://www.youtube.com/watch?v=bjhKTqdxRdo

It's like all the leetcode bullshit. We know that is not a valid measurement for actual performance in a dev job, but that doesn't stop managers from using it.

What they need is a number, a rating, on how much of a fit each candidate is, through some process that can be described as objective and fair. The algorithms provide that.

If we make this illegal, they'll just come up with some other bullshit.

In an ideal world, companies would assess each and every candidate individually and on their merits. But no-one has time or patience for that, so we have these bullshit systems.

"We only attempt to identify adverse impact based on self-reported racial information and do not impute data, noting that we do not have access to features like applicant name. 62.35% of all applicants in the data do not self-report race as belonging to one of the four racial groups we study."

Step two: These decision makers must be held accountable for the success of the process. Many companies fail this simple task.

Step three: These decision makers must be willing to admit that they made a mistake, and risk loss of prestige and political capital. Guess how likely that is.

And the bigger the company, the worse it gets. It's a good thing we didn't go through 20 years of consolidations and mergers. Oh wait.

We don't know how to measure worker productivity -> its hard to even say what a good hire is.

We don't have good standardisation around whatever measurements we do take -> hard to say anything about hiring at all.

People are more interested in their own prestige than hiring the best option for the company -> too many candidates get hired in the wrong places.

many of these problems do seem solvable given risk taking and statistics. However, culturally hiring managers aren't inclined to do either.