That's the mode of use for ML in most industries -- flagging stuff for follow-up by humans. Basically anything that's not real-time works like this. Most uses

That's the mode of use for ML in most industries -- flagging stuff for follow-up by humans. Basically anything that's not real-time works like this. Most uses of ML in real-time settings look more like hybrid systems -- a little dusting of ML on top of a whole heap of more traditional mathematical modeling/software engineering. Outside of a few very niche settings, we're still a long way off from "trusting" ML in any meaningful sense.