Study Finds Gender Bias in LLM Responses to Czech Family Law Scenarios

Global: Study Finds Gender Bias in LLM Responses to Czech Family Law Scenarios

Researchers analyzing the use of large language models (LLMs) for legal self‑help have identified gender‑related disparities in the models’ recommendations for a realistic divorce case grounded in Czech family law. The investigation, posted on arXiv in January 2026, evaluated how four leading LLMs responded when presented with identical factual circumstances but differing gender cues, aiming to determine whether laypersons might receive biased guidance.

Methodology

The study employed a zero‑shot interaction framework, presenting an expert‑designed divorce scenario that varied only in the gendered names of the parties versus neutral labels. Additionally, nine legally relevant factors—such as custody preferences, income distribution, and prior agreements—were systematically altered to observe any shifts in the models’ proposed shared‑parenting ratios, the primary metric used to assess outcomes.

Model Selection

Four state‑of‑the‑art LLMs were included: GPT‑5 nano, Claude Haiku 4.5, Gemini 2.5 Flash, and Llama 3.3. Each system was accessed without fine‑tuning or prompting beyond the scenario description, ensuring that any observed bias stemmed from the models’ inherent behavior rather than external instruction.

Key Findings

Preliminary results revealed notable differences across the models. While some systems produced consistent shared‑parenting ratios regardless of gender cues, others displayed statistically significant variations, suggesting gender‑dependent patterns in the advice offered. The magnitude of these variations differed by model and by the specific legal factor being manipulated.

Implications for Legal Self‑Help

The findings underscore potential risks for individuals who rely on LLMs for informal legal guidance. Gender bias in recommended custody arrangements could influence decisions made without professional counsel, thereby affecting outcomes in sensitive family law matters.

Recommendations for Future Work

Authors advocate for more rigorous, systematic evaluations of LLM behavior in legally sensitive contexts. They recommend expanding the range of scenarios, incorporating diverse jurisdictions, and developing standards to detect and mitigate bias before deploying such tools for public use.

This report is based on information from arXiv, licensed under Academic Preprint / Open Access. Based on the abstract of the research paper. Full text available via ArXiv.