That's a a bit too absolute way to look at it.

From their point of view the goal isn't to abolish human involvement, but to minimise the cost. So if they can do the job at the same quality with a quarter of the personnel through AI assistance for less cost, obviously they're gonna do that.

At the same time, just because humans having crappy jobs is the current way we solve the problem of people getting money, doesn't mean we should keep on doing that. Basic income would be a much nicer solution for that, for example. Try to think a bit less conservatively.

The bot demonstrated very well what this article is about. I don’t know the internals, but I also can’t image the bot was using the best and most expensive ways of doing analysis.

It was pretty bad at “getting the point” even when it was obvious, a better system should be able to do so. Sometimes the point is more difficult to discern and there has to be some judgement, you can see this in comments sometimes where people discuss what “the point” was and not just the data. I imagine an AI would have some difficulty determining what is worth summarizing in these situations especially.

I'm not sure how long ago that was, but LLM context sizes have grown exponentially in the past year, from 4k tokens to over a hundred k. That doesn't necessarily affect the quality of the output, although you can't expect it to summarize what it can't hold on memory.

That's very likely the case. LLMs sucking up all the air in ML research right now, and we shouldn't be using them as a hammer for every problem.

people doing more work is actually more expensive because human time is by far the biggest cost for most businesses

A test of AI for Australia's corporate regulator found that the technology might actually make more work for people, not less.