“Real problems” aren’t something that can be effectively discussed in the time span of an interview, so companies concoct unreal problems that are meant to be good indicators.
On that, these unreal questions/problems are decent proxies for general knowledge for humans, but not for AI. Humans don't have encyclopedic knowledge, so questions on a topic can do a decent job of indicating a person has the broader depth of knowledge in that topic and could bring that to bear in a job. An AI can answer all the questions but can't bring that to bear in a job.
WE saw this last year with all the "AI can now pass the bar exam" articles, but that doesn't lead to them being able to do anything approaching practicing law, because AI failure modes are not the same as humans and can't be tested the same way.
Really? How short are your interviews, and how big are these Real Problems such that you can't get a sense of how your candidate would start to tackle them?
The “real problems” most companies want people to help solve involve the evolution of products that last for years, involve repeated design discussions, in depth research, and applying retrospective learning. I don’t need someone that can just glue a Rails API together. If I did, I can literally just download that from the internet for free.
If my problems could be solved in the time span of an interview, why would I waste my time doing that interview instead of just solving it?
Yeah, what you want is a General Intelligence that has learned the topic you care about. Google search returning an algorithm when you ask it doesn't mean that you shouldn't test candidates on that algorithm, since you still need a General Intelligence that knows it and not just the algorithm itself.
“Real problems” aren’t something that can be effectively discussed in the time span of an interview, so companies concoct unreal problems that are meant to be good indicators.
On that, these unreal questions/problems are decent proxies for general knowledge for humans, but not for AI. Humans don't have encyclopedic knowledge, so questions on a topic can do a decent job of indicating a person has the broader depth of knowledge in that topic and could bring that to bear in a job. An AI can answer all the questions but can't bring that to bear in a job.
WE saw this last year with all the "AI can now pass the bar exam" articles, but that doesn't lead to them being able to do anything approaching practicing law, because AI failure modes are not the same as humans and can't be tested the same way.
Really? How short are your interviews, and how big are these Real Problems such that you can't get a sense of how your candidate would start to tackle them?
The “real problems” most companies want people to help solve involve the evolution of products that last for years, involve repeated design discussions, in depth research, and applying retrospective learning. I don’t need someone that can just glue a Rails API together. If I did, I can literally just download that from the internet for free.
If my problems could be solved in the time span of an interview, why would I waste my time doing that interview instead of just solving it?
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This is the answer.
Let's not pretend 95% of companies are asking asinine interview questions (though I understand the reasons why) that LLMs can easily solve.
Let's go one step further: LLMs can't solve anything, but most interview questions are covered so much online that they'll parrot a passable answer.
Yeah, what you want is a General Intelligence that has learned the topic you care about. Google search returning an algorithm when you ask it doesn't mean that you shouldn't test candidates on that algorithm, since you still need a General Intelligence that knows it and not just the algorithm itself.