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Yeah, you'd think if they have the codes those should be more reliable than free text descriptions. I don't see a scenario where you'd want to do natural language processing instead of just relying on the code to figure out what to do.
Oh, I can see that scenario. Mine was a rhetoric question, as I've been working in the data-shipping field for the past few years.
Thing is, if there's a thousand power stations, there may well be a thousand different implementations + error codes, because for decades there was no need for a common method of error reporting.
The only common interface was humans. That's why all of these implementations describe errors in human-readable text. And I would bet a lot of money that they've already had to extraxt those error codes from text logs.
Writing them out in e.g. a standardized JSON format, requires standardization efforts, which no one is going to push for while individually building these power stations.
That's how you end up with a huge mess of different errors and differently described+formatted error codes, which only a human or human-imitating AI can attempt to read.
I mean, there's definitely things they could have done that are less artificially intelligent, like keyword matching or even just counting how many error codes a power station produces. And I'm not sure you necessarily want a blackbox-AI deciding what gets power and what not. But realistically, companies around the planet will adopt similar approaches.
Yeah that's a good point, if you have lots of disparate systems that don't have standard coding then the codes wouldn't be of much use. I can see how standardizing that sort of things would be a huge effort, so in that context the approach makes sense.
I also assume that the humans have the final say, but in most cases I imagine having the computer do the initial routing will get better results than doing nothing at all while humans figure out what the overall picture is.