- cross-posted to:
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- cross-posted to:
- [email protected]
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.
A business that relies on blackbox AI decision making, when dealing with people, cares not about being accurate or fair, and adopts technology on the fallacy / stupidity of appeal to novelty instead of analysing its overall impact.
IMO this practice should be forbidden.
AI filtering has the promise of selecting good candidates very efficiently, due to pattern recognition on a level not immediately obvious to humans. Unfortunately no company is going to train their own hiring models, and good ones don’t exist on the market. Everyone vaguely competent is chasing LLMs and image generation. Specialized, focused models are almost forgotten in the hype.
So they just go with a commercial “enterprise” tool which are as we all know utter shite. HR AI tools are even worse than your typical fake “AI”.
There are two additional issues, related to each other:
Based on that I think that a better approach would be to use the AI model to create a filter, that can be analysed and tweaked by human beings, and then use that filter to select candidates. They won’t do this though - because it screws with their “I did nothing!!! the ai did it!!” excuse to be unfair.
But the way that it is now, frankly? Better to ban it.
Damn, that’s an angle i hadn’t been considering–the “AI did it, not me!” accountability loophole. Air Canada was just attempting to pull that on a customer that was given wrong info by a customer service bot. They only managed to get Air Canada to make good on their offer for bereavement rates when they were taken to court. Thanks AI!
Two categories of issues at play here:
Companies will miss good talent when AI doesn’t prioritize the way they would otherwise have wanted, doesn’t understand candidate data, or AI hasn’t been trained how to prioritize on the areas a candidate has. With how quickly job markets can change it’s realistic a piece of software or website could rise in popularity and fall over the period of a few years and it might take that long to update and correctly test the damn AI models to recognize and prioritize. All of this should hurt the company and it’s their fault and will helpfully limit incentives to use AI or black box AI at least as was said above.
Accountability - In the US, it’s illegal now if you have an employment practice (hiring, promotions, firing, etc.) that while it can’t be proven directly or evidence doesn’t exist for a specific case to win in court (prima facie) it can be shown on aggregate to have discriminatory outcomes for protected classes(race, sex, ethnicity, religion, etc.). It’s often impossible to find a smoking gun of “we don’t hire Protected Class X”, but if it can be shown that your employment practices lead to a protected class having much worse outcomes in a company or group, something can be shown to have disparate impact which is illegal and must be remedied.
I fully expect many shittily-trained, poorly or not tested “tools” to be sold and implemented by companies who will eventually be sued for disparate impact. There will be a frenzy of related suits between companies and the AI tool companies.
Creative destruction indeed.