BIASINSPECTOR introduces the first end-to-end, multi-agent framework for detecting biases in structured data, addressing a critical security and fairness challenge in AI systems.

• Uses synergistic LLM agents to identify biases across diverse data types
• Overcomes limitations of existing techniques that require extensive human intervention
• Provides a generalizable approach that works across different datasets and bias types
• Enhances security posture by helping organizations proactively identify and mitigate unfair data patterns

This research matters because undetected biases in structured data can lead to discriminatory algorithms, compromising both security and fairness in critical applications like lending, hiring, and healthcare.

BIASINSPECTOR: Detecting Bias in Structured Data through LLM Agents