Recognition is a proposal

Why fluent text must not become authoritative academic intent without a signer-controlled assurance boundary.

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What changed the product

Critical academic terms recovered by direct video routing in the locked comparison.

Decision trace

Does readable English preserve the part of the question that changes the answer?

Locked direct-video comparison · 20 public clips · 91 critical terms

Observed

The output sounded plausible.

The model returned fluent fragments from public ASL video. Fluency made the missing meaning harder—not easier—to notice.

Modern systems can produce readable language even when the underlying signed meaning is incomplete or wrong. Fluency can hide the failure.

Across the locked comparison, the direct general-video path recovered none of 91 predeclared meaning-bearing terms and never abstained. That result does not condemn multimodal AI. It rejects unverified direct routing for this academic workflow.

Sign First treats every recognition output as a candidate. Academic-risk checks focus on details that can change the task, and the learner remains the authority who can repair or approve the meaning.

The long-term target is not permanent blanket confirmation. It is calibrated selective intervention supported by independent evidence.