The basics likely get you there, I don’t think the modern bureaucratic state is a particularly high bar to clear:
Measure your baseline, pick good metrics, build human-vetted ground truth, then work through false positives/negatives starting with the most egregious/surprising. Start in shadow mode until the system is clearly better, however you must define that to ensure trust/buy-in.
Any appeals process naturally falls victim to the original problem, and so we're back where we started. And if you don't have an appeals process, how can you flag if something is wrong?
You seem to be arguing that all processes are equivalent. This seems like an overgeneralization.
For example supporting you spend 10x and hire a bunch of the smartest people around to run this process. Do you agree that you could decrease wait times?
You can think of this in terms of labor productivity if it’s helpful. It’s not a fixed value. The hypothesis is that if AI can increase the labor productivity of claimants, it can increase the productivity of the administrators too.
I see what you mean, but whilst there aren't really repercussions if the claim is incorrect; but if a claim is incorrectly rejected or accepted, that is a significant problem.
Comments
The basics likely get you there, I don’t think the modern bureaucratic state is a particularly high bar to clear:
Measure your baseline, pick good metrics, build human-vetted ground truth, then work through false positives/negatives starting with the most egregious/surprising. Start in shadow mode until the system is clearly better, however you must define that to ensure trust/buy-in.
Any appeals process naturally falls victim to the original problem, and so we're back where we started. And if you don't have an appeals process, how can you flag if something is wrong?
You seem to be arguing that all processes are equivalent. This seems like an overgeneralization.
For example supporting you spend 10x and hire a bunch of the smartest people around to run this process. Do you agree that you could decrease wait times?
You can think of this in terms of labor productivity if it’s helpful. It’s not a fixed value. The hypothesis is that if AI can increase the labor productivity of claimants, it can increase the productivity of the administrators too.
I see what you mean, but whilst there aren't really repercussions if the claim is incorrect; but if a claim is incorrectly rejected or accepted, that is a significant problem.