Ask HN: Can verifiable honesty rebuild trust in AI systems?

1 point·renshijian··5 comments

We built a system that makes AI honesty measurable each response carries a determinacy score, deception probability, and ethical weight

Instead of “trust me,” the model says “check for yourself.”

I wonder — can this kind of transparency help rebuild trust in AI? Or does it just expose how uncertain intelligence really is?

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Thanks for reading — this project isn’t about “AI safety theater.” We’re experimenting with verifiable honesty: every model response carries its own determinacy, deception probability, and ethical weight

Instead of “trust me,” the system says, “check for yourself.”

We’re curious how the HN community sees this: Can trust in AI be engineered through transparency? Or does showing the uncertainty just make it harder to trust?

How does that let you check for yourself, though? Don't people still have to trust that the reported probabilities and weights are both meaningful and correct?

Also, people tend to be pretty bad at interpreting probabilities.

That’s a fair point — verification itself still depends on trust in the verifier What we’re trying to test isn’t absolute truth, but transparency under uncertainty You’re right that people often misread probabilities — but maybe that’s the point If we can see uncertainty, even imperfectly, it starts a different kind of trust Not blind faith — more like “I know what this system knows it doesn’t know.”

I’ve been thinking more about that — maybe verifiability doesn’t remove trust, it just changes where we place it Not in the system, but in the transparency of its process

Gotta see it in action.

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