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AI + Access to Justice Current Projects

Presentation to Indiana Coalition for Court Access

On October 20th, Legal Design Lab executive director presented on “AI and Legal Help” to the Indiana Coalition for Court Access.

This presentation was part of a larger discussion about research projects, a learning community of judges, and evidence-based court policy and rules changes. What can courts, legal aid, groups, and statewide justice agencies be doing to best serve people with legal problems in their communities?


Margaret’s presentation covered the initial user research that the lab has been conducting, about how different members of the public think about AI platforms in regards to legal problem-solving and how they use these platforms to deal with problems like evictions. The presentation also spotlit the concerning trends, mistakes, and harms around public use of AI for legal problem-solving, which justice institutions and technology companies should focus on in order to prevent consumer harms while harnessing the opportunity of AI to help people understand the law and take action to resolve their legal problems.

The discussion after the presentation covered topics like:

  • Is there a way for justice actors to build a more authoritative legal info AI model, especially with key legal information about local laws and rights, court procedures and timelines, court forms, and service organizations contact details? This might help the AI platforms, avoid mistaken, information or hallucinated details.
  • How could researchers measure the benefits and harms of AI provided legal answers, compared to legal expert-provided legal answers, compared to no services at all? Aside from anecdotes and small samples, is there a more deliberate way to analyze the performance of AI platforms, when it comes to answering peoples questions about the law, procedures, forms, and services? This might include systematically measuring how often these platforms make mistakes, categorizing exactly what the mistakes are, and estimating, or measuring how much harm emerges from these mistakes. A similar deliberate protocol might be done for the benefits that these platforms provide.

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