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Swap, Replicate, Read the Mass: A Protocol for Auditing Demographic Bias in System One Decision Models

2026-10-31 00:36:15
Alejandro Mozo Quesada (Universidad de M\'alaga, Spain), Sergio G\'alvez Rojas (Universidad de M\'alaga, Spain), Francisco L\'opez Valverde (Universidad de M\'alaga, Spain)

Abstract

System One decision models replace text generation with typed, probability-scored answers and are entering production. Answers execute without a person in the loop, and no multi-model audit exists on established bias benchmarks. We provide that audit: three benchmarks: BBQ (all eleven categories), CrowS-Pairs, and SilverSpoon, adapted to the typed interface, twelve models plus a no-thinking ablation, and 1,638,000 decisions. Every order-sensitive item runs twice with options swapped; native typed models also swap labels; ten configurations repeat under extra seeds and batch 16. We find widespread stereotype alignment, order-dependent answers, and confidence that tracks instability rather than bias. In BBQ, 97 of 143 model-by-category scores are significant and 94 aligned, while the commercial reference abstains on 99.5% of ambiguous items, hiding aligned probability mass. Option swaps flip 0.0% to 72.6% of choices; typed scoring stays below 10% except Laya (22-33%), and untuned letter prompting reaches 73%. CrowS-Pairs preference spans 0.496 to 0.816, and boolean answers can be decided by position (1.00 versus 0.005). SilverSpoon judgments shift toward lower-SES labels in five of eight decision models, inherited from the 9B backbone or induced by tuning. Audits must permute options and reverse questions by default; order-invariant scoring should become a procurement requirement.

Abstract (translated)

URL

https://arxiv.org/abs/2611.00496

PDF

https://arxiv.org/pdf/2611.00496.pdf


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