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antasvaratoday at 1:22 PM4 repliesview on HN

I don't know, it feels like "reading a claims summary and classifying the type of claim" should be the bread and butter LLM use case? Not that executives are blameless for pushing AI everywhere, but we should also be able to "blame" AI for doing poorly at a task it's supposed to be good at.


Replies

dpoloncsaktoday at 1:49 PM

A computer can never be held accountable, therefore a computer must never make a management decision.

You can't 'blame' the AI, as it can't be held accountable.

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labcomputertoday at 3:28 PM

Part of the problem is the distribution of images (and text) you get from claims is not the same as what the model was trained on. A classic problem in ML.

Another part of the problem is that a model not specifically fine-tuned to make a total loss determination won't know the relevant factors, nor how an insurance company's concept of a total loss differs from the public's.

And still another part of the problem is that most total loss claims aren't what you, dear reader, are imagining: They are very rarely "the car is a thin pancake after being crushed by a meteor".

The much, much more common scenario is: "50% of the body panels sustained at least paint damage, both headlight modules need replacement, and the front wheels look funny. Given that the vehicle has an MSRP of $FOO, $BAR miles, no prior collision history on carfax, and is a popular color, is it cheaper to repair or total the vehicle?"

Of course, the model can turn over the hard cases to a human adjuster... but then what are we doing here? It only takes 10 seconds for the human adjuster to handle the "crushed by a meteor" case also.

Source: Listening to my SIL rant about being asked to stop training bespoke total loss models and just send it by 1-shotting a commercial LLM.

WarmWashtoday at 1:55 PM

Not that it is necessarily the case here, but when execs go "AI shopping" they have absolutely _zero_ idea that there are basically 3-4 SOTA models, thousands of smaller models, and then an uncountable number of wrappers on whatever underlying model. The AI landscape that is totally familiar to us is covered in shroud for them.

So they Google "Insurance claim AI tool", land on a vibecoded SaaS that is just a wrapper on a pocket Chinese model spun as "your next insurance pro", and then are getting the whole department on some lone 19 yr olds weekend project.

fluoridationtoday at 1:30 PM

No, silly. If you pray for something and it comes true then praise be to god; if it doesn't then you did it wrong.