What if you want errors to happen, e.g. deny care, bomb civilians; in that case 90% error rate is what you want, and plausible deniably so!

> the situation would have to be very particular

The situation is very particular. When the system makes an error, I make a bigger profit. If the system made fewer errors, it would approve more things that cost me money.

Why do you think I'm motivated to make fewer errors under that situation?

Nah, it's cumulative errors per claim. E.g. maybe the per-decision-factor rate is somewhere over 50% but overall most claims will have errors because so many factors go into coverage/reimbursement decisions.

> if you have a system that makes errors over 90% of the time then you have a system you can leverage to make fewer errors.

Sure if you're flipping a coin.

If you're calculating a number from 1 to 100 then depending on distribution a calculation that's wrong 90% of the time is probably useless.

It sounds like something with a 90% error rate would be better to just do the opposite of what was determined and suddenly have a 10% error rate??

I can easily build you a system that will guess the price of a stock tomorrow wrong at least 90% of the time. Even 100% wrong if you'd like. How would you use that to make fewer errors in some other system?

What makes you think they are financially motivated to make fewer "errors" (improper denial of care while keeping premiums)?

> if you have a system that makes errors over 90% of the time then you have a system you can leverage to make fewer errors.

member the three words "delay, deny, depose"? Insurances - and not just in the US, Germany has similarly bad stuff going on - aren't making a profit if they just blindly accept claims. It is much more profitable to deny with a vague "AI" system (or a blanket automated deny) first, and only have a first look with an actual human agent at it when the customer complains or files a lawsuit.

https://en.wikipedia.org/wiki/The_purpose_of_a_system_is_wha...