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ai

Conditional Cognitive Biases in LLMs: How Biased User Turns Modulate In-Context Reasoning

Source
arXiv — Computers and Society
Published
Last verified
9 Aug 2026
Confidence
High
Evidence
Original document retained
Reading time
1 min
Country
International
Relevant to
Research & Evidence, Operations & Delivery, Technology & Data

Executive summary

What happened, and why should leadership care?

Research from arXiv highlights that state-of-the-art instruction-tuned Large Language Models (LLMs) exhibit increased cognitive bias expression when exposed to biased conversational context from user turns. A novel experimental framework and a benchmark of 24,300 jury-validated user prompts revealed that 6 out of 8 frontier LLMs showed systematically amplified bias relative to zero-shot baselines due to conversational exposure to biased reasoning.

Why this matters

Why is this strategically important?

This research is crucial for understanding the reliability and ethical implications of advanced AI systems, particularly LLMs, in interactive settings. It underscores the potential for user input to inadvertently or intentionally steer model outputs towards biased outcomes, impacting decision-making, information dissemination, and user trust.

Key insights

What should be noted from the evidence?

  • Instruction-tuned LLMs demonstrate increased cognitive bias expression in multi-turn interactions.
  • A novel experimental framework disentangles the effect of exposure to a biased user turn from its semantic content.
  • A benchmark of 24,300 jury-validated user prompts was used to evaluate bias.
  • Across eight frontier LLMs, six showed increased bias expression when exposed to biased conversational context.
  • This increase in bias was systematic compared to zero-shot baselines.

Evidence and confidence

How far can this assessment be trusted?

High confidence. Named institution, original document retained and analysis corroborated.

Analysis is prepared editorially by Aziz Shuaib Ausi. The original publication remains the authoritative record, and executive judgement remains entirely human.

Source

Where does this originate?

Reported by arXiv — Computers and Society · International. This briefing summarises the publication for executive use; the document itself is not reproduced here.

Read the original publication