[gbro3n]

The most sensible use for AI that I can see at this time is for supporting humans in their work, but only where the system is set up so that the human has to do the work first, with the AI system looking for possible errors. For example the human drives the car, and the AI brakes when it senses dangerous conditions ahead, or the human screens test results for evidence of cancer and the AI flags where it disagrees so that the human might take another look. The opposite scenario with AI doing the work and humans checking for errors as is the case here will lead to humans being over reliant on less than perfect systems and producing outcomes with high rates of error. As AI improves and gains trust in a field, it can then replace the human. But this trust has to come from evidence of AI superiority over the long term, not from companies over-selling the reliability of their AI.

[uh_uh]

Humans are also less than perfect systems. Especially if they have to deal with monotonous tasks. A human might perform better on a 100 entries than an AI, but on 10 thousand? Of course you can distribute the workload, but you will balloon the costs (I'm talking about a future where GPT3 costs come down).

There must be a set of projects which are cost prohibited now due to having to pay humans but will become feasible exactly because of this tech. For a good portion of these, higher-than-human error rate will also be tolerable or at least correctable via a small degree of human intervention.

[visarga]

> A human might perform better on a 100 entries than an AI, but on 10 thousand?

There's also increased variance in human accuracy. You might train 100 but 10k people? A model is consistent all the way.

[gbro3n]

This is a good point. There is some work that just wont be done unless it can be automated, and in that case work with a higher rate of error is preferable to no work at all.

[armchairhacker]

This won’t work because humans are lazy and fundamentally wired to expend the least amount of effort possible. Just the belief that you have an AI that will correct your mistakes, will make people expend less effort (even subconsciously), until it completely cancels out any additional error correction from the AI. Plus, workers will hate the fact that an AI could automatically do exactly what they are doing but they are doing it manually for “error correction”.

It only works the opposite way, where machines and AI handle the trivial cases and humans handle the non-trivial ones. Many people actually genuinely like to solve hard problems which require thinking and skill, most people strongly dislike mundane repetitive tasks.

[RodgerTheGreat]

Humans may find, however, that without practice solving the trivial problems they are ill-prepared for the difficult ones.

[andreilys]

So humans should do the work of image classification, voice transcription, text summarization, etc. before an AI gets involved?

Makes total sense to me.

[gbro3n]

"As AI improves and gains trust in a field, it can then replace the human. But this trust has to come from evidence of AI superiority over the long term"

[quickthrower2]

Often the other way around is better. Example: Let AI give text classification a go then let a human perfect and check the result. Let AI end your email but check you are happy with how it is physically phrased. Etc.

Human first scenarios will be more rare. And probably where the human has to do it by law. Made up example: border control checking passport photos match face. Human checks and if they click OK then AI double checks.

[potatoman22]

One could argue that AI finishing emails is a progression of AI proofreading emails

[leereeves]

I mostly agree. Happily, that's also what people will want as long as human participation is necessary. We'd generally prefer to write rather than correct an AI's writing, and prefer to drive rather than carefully watch an AI drive.

But when the AI is capable of something the person can't do (like Stable Diffusion creating images compared to me) the AI should take first chair.

[gbro3n]

This is a good point. Where less than perfect AI is better than the alternative, it is useful.