Comment by 2bsinha

Are AI failures really model problems, or governance problems?

Over the past year, we’ve seen AI systems hallucinate in courts, leak internal prompts, get manipulated by praise, or make decisions they were never meant to make.

Most discussions focus on:

better models

alignment

prompt design

But I’m starting to think many of these failures aren’t intelligence issues at all.

They’re governance issues.

In most real systems, we separate:

capability from permission

intelligence from authority

generation from action

AI systems often skip this and let agents act by default, then try to clean up afterward with filters.

Curious how others here think about:

eligibility checks before AI actions

graduated authority for agents

limiting influence rather than outputs

system-level governance outside the model

Is anyone building or experimenting with this kind of control layer?