> Generally, chatbots function in direct communication with humans and do not function autonomously. Thus they are dependent on not just human meaning-making but human thirst for meaning which will find it even when it isn't there.

The latter doesn't follow. They may just be dependent on good prompt design.

People who aren't used to the AIs, and don't know how to use them, get worse results. This shouldn't be a surprise; it's how every tool works.

> Most literature on the subject points out the importance of a "human in the loop"

What most literature fails to capture is that different humans work on varying level of complexity tasks.

A person that consistently find a bot useful in their job then the job is easily replaceable.

If someone doesnt then good news - that job is safe.

The prompt is everything. It’s sort of like knowing how to formulate a google search query, but cubed. You need to learn a whole bag of tricks and you can’t use the intuitions of talking to people for talking to the AI. Some people are by now really adept at prompt engineering and that makes them skilled at setting the AI to work.

That’s why people’s first impressions are often so wildly off. People who have the fortune of asking the right prompts for their first conversations walk away believing they’ve spoken to AGI, people who ask a less than optimal prompt (or things it is bad at like math problems) walk away not seeing what the hype is about.

Same thing with copilot. The quality of the code that it suggests depend a lot on the context, so if someone isn’t writing good comments and giving their variables proper names the suggested code will be terrible.

These systems are very capable, but using them is a skill that must be learned, and there’s little material out there to teach that skill because things move so quickly.