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[ARTICLE · art-94167] src=discuss.huggingface.co ↗ pub= topic=ai-ethics verified=true sentiment=· neutral

An open, model-agnostic "interaction card": verifiable provenance for AI decisions

The author of an open, work-in-progress format called "Causal Seal" proposes a model-agnostic "interaction card" that binds a SHA-256 fingerprint to an AI output, its causal parameters (model identity, constraints, context, timestamp), and the moment of emission, enabling verification without access to the model. The format is open (CC BY 4.0), vendor-neutral, and available via `pip install causal-seal`, with a browser verifier, aiming to complement model cards by documenting individual decisions rather than the model itself.

read1 min views1 publishedAug 12, 2026

I’m the author of an open, work-in-progress format for the provenance of AI

decisions, and I’d love feedback from this community — model cards are, in a

sense, the ancestor of what I’m building, and HF champions open, model-agnostic

documentation.

The gap. Model cards document the model. There’s still no open way to

verify how a specific output was produced.

The idea. A “Causal Seal” attaches to a single output a small record that

binds — into a SHA-256 fingerprint — the output, the causal parameters that

governed its generation (model identity, constraints, context, timestamp), and

the moment of emission. Anyone can verify it with no access to the model or

any private system. It’s open (CC BY 4.0) and privileges no vendor. Think of it

as the per-decision, verifiable counterpart to a model card — an “interaction

card.” Complementary, not competing.

What already exists (public, reproducible): pip install causal-seal

) and a browser verifierMy questions:

Any feedback is welcome — this is early, single-maintainer, open work.

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