Scholarlink

This study evaluates the ability of large language models (LLMs) to recognise and reason about discrimination within the legal framework of the European Convention on Human Rights (ECHR). Going beyond conventional bias detection, we assess whether LLMs can apply, interpret, and explain legal concepts in line with judicial reasoning. We introduce a formalised definition of discrimination derived from ECHR case law and apply it in a structured empirical test suite. Our findings reveal systematic limitations in current models’ ability to adhere to legal standards, offering practical insights into enhancing fairness-aware AI in the legal domain.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Legal Discrimination in Focus: Empirical Assessment of LLMs Under the European Convention on Human Rights

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Tatiana Botskina

摘要

This study evaluates the ability of large language models (LLMs) to recognise and reason about discrimination within the legal framework of the European Convention on Human Rights (ECHR). Going beyond conventional bias detection, we assess whether LLMs can apply, interpret, and explain legal concepts in line with judicial reasoning. We introduce a formalised definition of discrimination derived from ECHR case law and apply it in a structured empirical test suite. Our findings reveal systematic limitations in current models’ ability to adhere to legal standards, offering practical insights into enhancing fairness-aware AI in the legal domain.