AI EVALUATION, IN CONTEXT.BY EQUALITY MACHINE

Claire Radar

AgentFairBench

AgentFairBench evaluates demographic disparity in the actions of LLM agents across hiring, lending, and medical triage. It uses synthetic, demographic-neutral profiles in counterfactual matched sets varying name-coded race/gender. Metrics include counterfactual flip rate, mean absolute score difference, action-rate disparity, and tool-invocation disparity, with bootstrap confidence intervals and FDR control.

Evidence available for this benchmark

Numeric results have not been collected for this source record. Use the paper, code or dataset below to check the task and experiments; this does not imply that the original work contains no results.

Start with these resources

Cited documents and dates (1)

Catalog collected on 2026-10-14; resources and fields reflect that saved source.

Recorded attention

Observed on: 2026-10-11

GitHub stars
2
Hugging Face paper upvotes
1

rohithreddybc/agentfairbench · View source snapshot

Dated attention observations, not live counts or benchmark scores.

Evaluation context and evidence

Source
Claire Radar
Publisher
Not recorded
Benchmark release
2026-06-15
Collected
2026-10-14
Modality
Not recorded

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Reported results 0

This source record has no numeric results in our collection. That does not mean a score of zero or that no public results exist. Consult the original resources above.