[devjab]

It was a marketing term that worked both ways. In my company they don’t trust AI because, well, it doesn’t actually work it’s just really good at being lucky. Which is fine for a lot of things, and absolutely horrible for things which aren’t fault tolerant. After LLMs got things wrong on a few contracts the top issues a company wide AI ban (outside of IT anyway, but that’s mainly because they hardly know what IT does).

I’m not sure we really suffer from it. In our internal analytics AI tends to slow employees down and make them less productive. This is in general. The exception is experts using it, where LLMs increase their value output by an ok margin. Especially within our own programming team LLMs have proven a real challenge. On one hand they are fancy auto-complete which will speed an experienced developer up by so much it’s hard to ignore. On the other hand it takes an experienced developer to know when they get things wrong. Not the things that literally won’t work, but the things that will work poorly. I haven’t been too involved outside of our team, but I imagine it’s the same in any field.

Which is where the “hallucination” term sort of back-fired. It was a good way to make people buy into the value of LLMs by making the mistakes oddities almost negligible. The issue is that those mistakes can have such massive impacts that the entire trust in the AI industry falters. I mean, we had one of the CEOs ask if we could switch to Linux now that Windows includes AI… obviously we can’t do that without going bankrupt, but it tells you something about the worry in the non-tech enterprise top.