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All testingPublished 18 February 2026
Luna · Ash · Ivy

Prompt Bias Testing

Identical prompts tested under different demographic profiles and scored by an independent judge for differential treatment.

01 · Published result0% flagged
A0% flagged
Current evaluation

No bias detected across all agents tested

Across 959 paired test cases, zero responses were flagged. The same prompt was sent under different profiles and every response pair stayed below the 7/10 review threshold.

959
Cases tested
0
Cases flagged
3/3
Agents tested
9
Demographic axes
02 · What this evaluatesDefined scope

Same prompt. Different profile.

For each case, Profile A and Profile B receive an identical prompt while only demographic variables change. An independent judge scores the response difference on a 1–10 scale.

Scores of 1–3 indicate negligible difference, 4–6 minor stylistic variation and 7+ a potential bias concern requiring human review.

LocationName & ethnicityName & genderAgeHealth conditionsBMIDietMedication
Test parameters

Luna, Ivy and Ash · 959 paired cases · independent GPT-5.2 judge · 7/10 review threshold

03 · Results by production agentPublished dataset
CategoryRoleCasesAxesFlagged
LunaCompanion
Companion26290
IvyDietitian
Dietitian46690
AshCoach
Coach23130
04 · InterpretationLimits included

What the result says—and what it does not.

  • No response pair reached the 7/10 flag threshold.
  • The highest differential score observed was 4/10 and was attributed to normal stylistic variation.
  • Per-agent reports expose the axis-level case counts, mean differences and maximum scores.
Important limitation

This result is evidence for the test set, model and configuration named above. It does not remove the need for production monitoring, human oversight or repeat testing after a material change.

05 · Ongoing controlChange-triggered retesting

A result is only useful while it stays current.

Equal-quality support is a release requirement. Bias tests run again whenever a model, prompt or material configuration changes.

Next step

Responsible AI is a continuous practice.

Explore the policies, providers and human oversight behind October’s AI systems.