A video showing beans being poured into a cup sitting atop of a scale, atop of another scale. Both scales measure the beans concurrently.
A video showing beans being poured into a cup sitting atop of a scale, atop of another scale. Both scales measure the beans concurrently.
I’ve always hated the phrase “trust but verify.”
It’s a nonsensical oxymoron. It’s like saying “I trust my wife not to cheat on me, but I verify it by having her followed.” Then you don’t trust your wife dude
I’ll get off my soapbox now.
It’s a risk management strategy where you only do checks afterwards.
“Trust” means that you don’t make processes wait on passing checks before proceeding, because that would be expensive and/or slow.
“Verify” means that you have a separate process that comes through and runs checks afterwards, maybe on only some of the things you trusted, to catch issues.
It’s ideal when you have high-volume and/or low-latency processes where failures are low stakes but you still want to catch systemic issues eventually.
It’s related to the idea that “the optimal amount of fraud is non-zero”.
It resolves if you realize that “trust” can refer to an action taken which will only turn out okay if the thing trusted is indeed trustworthy.
For example, a field agent reports that there’s a forbidden shipment of firearms passing through X port on such a such date.
“Trust but verify” in this situation means:
That’s my take on it at least. You take whatever action would be warranted if the intel is correct. But you also work to verify the intel (you just don’t wait for the confirmation to take action).
This is exactly it. The OPs analogy of his wife cheating needs a bit of a tweak because the assumption his wife is predicated on the fact that she was unfaithful at some point.
A lighter example might be trust your wife started the dishwasher. You verify that she did by checking the dish detergent door.