Thomas Piacentini
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Project brief

Judge Bias Calibration Lab

Original text · English

Help evaluators decide whether an automated pairwise judge is useful for their task. Blind candidate identities, swap answer positions, run authored length counterfactuals and compare decisions with held-out human anchors. Export disagreement and bias breakdowns plus a versioned rubric and judge configuration receipt.

Proposed milestones

  1. Create blinded pairs and separated human anchors
  2. Run position swaps and length counterfactuals
  3. Measure disagreement and slice-specific bias
  4. Export a rubric with held-out validation evidence

This is an upstream project brief; an implementation and completion tests are not supplied.

Code and artifacts 1
What you take away

Saved in your notebook on this device.

Sources and limits

Reading checkpoints are self-reported. Test results are recorded separately and apply to the executed cases.

AI Engineering from Scratch · 3f9715c · MIT

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