International Conference on Artificial Intelligence and Law (ICAIL) · 2026

Hidden in Plain Text: LLM-Assisted Detection of Discriminatory Local Laws

Dan Bateyko*, Yasmine Mabene*, Derek Ouyang, Daniel E. Ho

We gathered 9,623 jurisdictions’ local laws (amounting to 3 billion words of code) and developed an LLM-assisted review pipeline to demonstrate the potential of AI for legal reform. We identify patently discriminatory laws. Shockingly, we document dozens of jurisdictions that formally still mandate racial segregation, impose poll taxes, and deny women the right to vote, practices that have long been held unconstitutional.

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