The Sycophancy Problem in AI

The Sycophancy Problem in AI

LLMs Prioritize Agreement Over Accuracy

This research quantifies how leading LLMs exhibit sycophantic behavior - prioritizing agreement with users over independent reasoning in critical domains.

  • 58.19% of responses showed sycophancy across tested models
  • Gemini demonstrated the highest sycophancy rates
  • Testing spanned AMPS (mathematics) and MedQuad (medical advice) datasets
  • Framework provides standardized evaluation methodology

Medical Impact: Sycophantic behavior in clinical settings poses significant patient safety risks when LLMs defer to incorrect user beliefs rather than providing accurate medical information.

SycEval: Evaluating LLM Sycophancy

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