2025
Where Fact Ends and Fairness Begins: Redefining AI Bias Evaluation through Cognitive Biases
EMNLP 2025
Recent failures such as Google Gemini generating people of color in Nazi-era uniforms illustrate how AI outputs can be factually plausible yet socially harmful. AI models are increasingly evaluated for “fairness,” yet existing benchmarks often conflate two fundamentally different dimensions: factual