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A Rutgers University study published in Nature Machine Intelligence in 2026 reveals that large language models expend more reasoning tokens when processing counter-stereotypical information. Researchers Calvin K. Lai and Messi H.J. Lee tested five models, including OpenAI's o3-mini and Claude 3.7 Sonnet, finding that most echo human implicit biases during reasoning.
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