Question 1

If your system logs a human approving a wrong decision, haven’t you just built the plaintiff’s exhibit?

Accepted Answer

Discovery never turns on whether you kept records — in claims, clinical, and permitting you are already legally required to retain them. It turns on whether you ran a reasonable process. The case that loses is a foreseeable harm with no oversight trail: absence of documented review, not its presence. We produce the opposite artifact — evidence that the uncertain moments were flagged, that a named human engaged them, and that a recorded rationale stands behind each judgment.

Question 2

Do we have to replace our claims system, EDC, or permitting platform?

Accepted Answer

No. Human.Readable sits underneath whatever you already run. It is a layer, not a rip-and-replace, and it does not ask you to migrate a system of record.

Question 3

Will this make our AI model more accurate?

Accepted Answer

No — deliberately. Its entire value depends on that restraint: it exists to know when the AI it’s watching doesn’t actually know, not to make that AI guess better.

Question 4

How is uncertainty actually measured?

Accepted Answer

By asking the model the same question multiple times and measuring agreement across the answers. That catches disagreement-type uncertainty. Systematic error — where a model is confidently and consistently wrong — is caught by schema validation and an always-review guard on safety-critical fields such as adverse event grade, denial reason code, and violation category. A low entropy score can never let a genuinely critical field skip review.

Question 5

Which regulations does this help us meet?

Accepted Answer

Current AI-in-claims statutes — Indiana HB 1271, Alabama SB 63, and Maryland HB 820 — mandate human review and disclosure, and increasingly audit, inspection, or annual certification. None mandates a per-decision audit artifact. Human.Readable is the cheapest, most defensible way to prove the review those laws already demand. In clinical work it maps to 21 CFR Part 11, ALCOA+, and ICH E6(R3).

Question 6

Does the audit trail leave the product?

Accepted Answer

Yes. The provenance ledger exports to CSV as a standalone audit artifact, so a regulator or auditor can read it without being given an account.

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