You do realize that when you have to find a special use case to defend something you are really giving an argument AGAINST casual widespread use of it.
You do realize that when you have to find a special use case to defend something you are really giving an argument AGAINST casual widespread use of it.
I disagree. It would be a wonderful world where every overseas contractor that I interacted with used the AI tools in this fashion.
Even among native speakers, literacy is way down. AI could help with that… if people actually do the work.
That’s the real problem, not AI: no one wants to do the work. That is purely a PEBKAC situation.
Science says the opposite, sorry. People lose their language skills when they outsource their thinking to AI. You can believ what you want want but that doesn't change the facts.
Pretty sure the references you are referring to are about losing coding skills, which is a very different set of skills than language skills. The kagi link (1) a sibling comment left was an example of an AI that can improve writing while also informing about better writing style. As opposed to the slop grenade, which is outsourcing thinking to AI.
1. https://news.ycombinator.com/item?id=48219992#48221497
The point is, you don't have to outsource your thinking to use AI, if it's a good AI tool. But most AI companies are coming from a hyper-scaling mindset where addicting the user to the product is the same as substituting hard thinking for easy dopamine hits. The most ridiculous benchmark I have seen in AI is the tendency to say the longer an agent can work and some minimal accuracy is a good thing. That just means you have 30 steps to find an error in instead of 3, and you are much more likely to just abdicate thought instead of the hard work of proofing 30 steps yourself. AI companies and evaluators are losing the point.
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