Allen Institute Launches FairStress Benchmark to Expose Hidden Bias in LLM Decisions
Allen Institute for AI (Ai2) released FairStress, a benchmark that tests demographic fairness in LLMs not just by their final decisions but by how easily those decisions change under persuasive pressure. Testing open and frontier models including Olmo, Llama, Qwen, Gemma, Claude, and GPT found that models often abandon correct, well-supported decisions more readily when doing so favors a minority-coded candidate — a pattern the authors call 'anti-stereotypical over-correction.' The benchmark covers 300 scenarios across 29 domains (hiring, lending, healthcare, education, housing, criminal justice), expanded via demographic and persuasion variations into over 13 million test cases, plus a smaller 50K-item 'FairStress-Core' subset for faster evaluation.