Except hammers already do not work as expected 100% of the time, as evident by them painfully hitting the hands of the workers in mishaps. Yet we still use them.

How is a hammer "not working as expected" if you hit your hand with it? This makes no sense. If I hit my hand with a hammer, what am I supposed to expect except causing pain and injury?

If I try to light a cigarette and accidentally set my beard on fire due to my own clumsyness, did the lighter malfunction? No, the lighter did exactly what it was supposed to do, it was my hand that didn't do what I expected.

If you want to continue with semantics, the worker did not expect to hit his thumb until the hammer bounced off of it, hence the tool did not work as expected. Until regular hammers are able to put nails into wood by themselves, we are talking about the success of the complete system that includes both the hammer and its user.

Either way, when working with humans we already deal with plenty of misses and mistakes. Programmers create 10 to 20 bugs per 1000 lines of code, 9 out of 10 businesses fail, accountants make detrimental blunders, etc.

The point is that in the end the ML systems need only to replace these already non-perfect systems. I'll refrain from judging the consequences of this as I think it's out of scope.

Nice packpedal, except now what you said makes no sense anyway because the discussion was about tools doing what you expect them to do, not "tool + human systems" doing what you expect them to. These are two different things.

Do you think a carpenter who hits themselves with a hammer blames the hammer or themselves? Or are you going to unironically tell me they would blame the hammer + human system?

Do you have a more specific point you're trying to make?

The discussion is about AI partially replacing human colleagues. In practice, people already are not 100% reliable. You make a reasonable request and someone makes a stupid blunder instead. That's the "hammer" hitting your thumb. Maybe you were not specific enough or maybe they didn't listen but the damage is done.

Our work processes already take mistakes and iterative refinement into account. If AI, in some specific niche, is cheaper and makes no more mistakes than humans do, it gets the job.

It doesn't need to be perfect or perfectly reliable. Some guardrails will be built into it, and we'll come to trust over time.

>not "tool + human systems" doing what you expect them to. These are two different things.

Please explain how?

>Or are you going to unironically tell me they would blame the hammer + human system?

As your tooling gets more complex, yes it is very easy to have a non-zero blame assignment to each party. Look at any human+machine system where complex failure conditions can occur.

You want me to explain the difference between a hammer and a human wielding one?

One is a hammer. The other is a human wielding a hammer.

> Except hammers already do not work as expected 100% of the time, as evident by them painfully hitting the hands of the workers in mishaps. Yet we still use them.

The hammer did work 100% as expected. It's the human, who is fallible, that hit their hand with the hammer. My analogy stands. We make mistakes, we want tools that do not. LLMs should not be compared to humans, they should be compared to other tools.

To a company a person is a tool. "Human resources" means exactly what it says.