I kinda disagree. High risk environments just means that they will have to have a human-in-the-loop for a longer time which drastically reduce the skill required for such human (which is still requires high skill just not stupidly high).
I kinda disagree. High risk environments just means that they will have to have a human-in-the-loop for a longer time which drastically reduce the skill required for such human (which is still requires high skill just not stupidly high).
The employers will think it requires less skill, whereas in fact it might actually require more skill to do a good job of being the human-in-the-loop.
For example, my sister is a translator and she says that checking AI translations is actually harder in many ways than doing a translation in the first place, but the agencies pay less for checking than actual translation.
I used to do audio transcription and some video captioning. Found it a bit drudgerous and fatiguing in rather specific ways, but I was effective at it and could find some satisfaction in it. It's been some years now, so I haven't had a chance to try out the kind of thing they're doing now, but I'm pretty sure I wouldn't want to. I can raise my blood pressure just sitting here and thinking about what it would be like to have to go through a Word doc and correct the bot's errors. But, even putting aside my professional pride (or indignation), I can only imagine that it would make all kinds of mistakes I never would, and wouldn't be any help with the parts I'd have trouble with. And I'm pretty sure that, at least often enough for it to be an issue, the priming of reading what the bot thought something was could easily make it way harder to hear it correctly, if I notice there's something wrong in the first place. I assume there's a similar problem for your sister along the lines of throwing off how it would occur to her to express something in the target language.
Doesn't it increase the skill required? You need to be able to jump in at the perfect time, while waiting patiently for 99% of the time. It's like self-driving that requires you to "jump in" at the worst possible time (0.5 seconds from a crash), and stay put the rest of the time--but don't get bored or inattentive. The only way to do that would be to be so naturally good at the danger point that you can do it basically reflexively.
I think the opposite, only the most skilled will be required.
But it depends on the skill:
- For landing pages & simple saas solutions: marketeers & founders have more skill, since they understand the user best. The real skill is not the basic coding, but understanding the market.
- For security risks/architecture: senior devs can spot things in seconds
Im not a doctor or lawyer, but im sure there are cases where AI is really good in a similar way and cases where they miss the most crucial aspects.
> drastically reduce the skill required for such human
I mean thats what is wanted by some companies.
The problem, especially for things like legal is that it requires someone more skilled to read through and understand that the argument is bollocks, or the law/precedent they are banking on is in fact the right one.
We have a tool that auto-writes letters to our management companies when they break SLAs. We have a slider that goes from polite to we are going to extract your first born.
Thats simple ish to do for LLMs, and low risk.
Drafting contracts is also something we could probably do, as its mostly boilerplate. However the consequence for mis-drafting a contract is multi-million dollars.
Man, this comment made me think of a Kafkaesque future where two AI lawyers and an AI Judge are stuck in an infinite loop arguing over a case, meanwhile the defendant is running around trying to get anyone in the legal system to recognize that the AI is stuck.
If the human involved has no skill then they might as well not be there, since they're just a fall guy when things go wrong and won't do anything to prevent it from happening.
I said that still requires skill, just not as much.
The end game of this is just a human capable of taking the blame when AI makes an occasional mistake and being paid for that service and risk.