AI + Access to Justice Current Projects

AI & Legal Help at Codex FutureLaw

At the April 2024 Stanford Codex FutureLaw Conference, our team at Legal Design Lab both presented the research findings about users’ and subject matter experts’ approaches to AI for legal help, and to lead a half-day interdisciplinary workshop on what future directions are possible in this space.

Many of the audience members in both sessions were technologists interested in the legal space, who are not necessarily familiar with the problems and opportunities for legal aid groups, courts, and people with civil legal problems. Our goal was to help them understand the “access to justice” space and spot opportunities to which their development & research work could relate.

Some of the ideas that emerged in our hands-on workshop included the following possible AI + A2J innovations:

AI to Scan Scary Legal Documents

Several groups identified that AI could help a person, who has received an intimidating legal document — a notice, a rap sheet, an immigration letter, a summons and complaint, a judge’s order, a discovery request, etc. AI could let them take a picture of the document, synthesize the information, present it back with a summary of what it’s about, what important action items are, and how to get started on dealing with it.

It could make this document interactive through FAQs, service referrals, or a chatbot that lets a person understand and respond to it. It could help people take action on these important but off-putting documents, rather than avoid them.

Using AI for Better Gatekeeping of Eviction Notices & Lawsuits

One group proposed that a future AI-powered system could screen possible eviction notices or lawsuit filings, to check if the landlord or property manager has fulfilled all obligations and m

  • Landlords must upload notices.
  • AI tools review the notice: is it valid? have they done all they can to comply with legal and policy requirements? is there any chance to promote cooperative dispute resolution at this early stage?
  • If the AI lives at the court clerk level, it might help court staff better detect errors, deficiencies, and other problems that better help them allocate limited human review.

AI to empower people without lawyers to respond to a lawsuit

In addition, AI could help the respondent (tenant) prepare their side, helping them to present evidence, prep court documents, understand court hearing expectations, and draft letters or forms to send.

Future AI tools could help them understand their case, make decisions, and get work product created with little burden.

With a topic like child support modification, AI could help a person negotiate a resolution with the other party, or do a trial run to see how a possible negotiation might go. It could also change their tone, to take a highly emotional negotiation request and transform it to be more likely to get a positive, cooperative reply from the other party.

AI to make Legal Help Info More Accessible

Another group proposed that AI could be integrated into legal aid, law library, and court help centers to:

  • Better create and maintain inter-organization referrals, so there are warm handoffs and not confusing roundabouts when people seek help
  • Clearer, better maintained, more organized websites for a jurisdiction, with the best quality resources curated and staged for easy navigation
  • Multi-modal presentations, to make information available in different visual presentations and languages
  • Providing more information in speech-to-text format, conversational chats, and across different dialects. This was especially highlighted in immigration legal services.

AI to upskill students & pro bono clinics

Several groups talked about AI for training and providing expert guidance to staff, law students, and pro bono volunteers to improve their capacity to serve members of the public.

AI tools could be used in simulations to better educate people in a new legal practice area, and also supplement their knowledge when providing services. Expert practitioners can supply knowledge to the tools, that can then be used by novice practitioners so that they can provide higher-quality services more efficiently in pro bono or law student clinics.

AI could also be used in community centers or other places where community justice workers operate, to get higher quality legal help to people who don’t have access to lawyers or who do not want to use lawyers.

AI to improve legal aid lawyers’ capacity

Several groups proposed AI that could be used behind-the-scenes by expert legal aid or court help lawyers. They could use AI to automate, draft, or speed up the work that they’re already doing. This could include:

  • Improving intake, screening, routing, and summaries of possible incoming cases
  • Drafting first versions of briefs, forms, affidavits, requests, motions, and other legal writing
  • Documenting their entire workflow & finding where AI can fit in.

Cross-Cutting action items for AI+ A2J

Across the many conversations, some common tasks emerged that cross different stakeholders and topics.

Reliable AI Benchmarks:

We as a justice community need to establish solid benchmarks to test AI effectiveness. We can use these benchmarks to focus on relevant metrics.

In addition, we need to regularly report on and track AI performance at different A2J tasks.

This can help us create feedback loops for continuous improvement.

Data Handling and Feedback:

The community needs reliable strategies and rules for how to do AI work that respects obligations for confidentiality and privacy.

Can there be more synthetic datasets that still represent what’s happening in legal aid and court practice, so they don’t need to share actual client information to train models?

Can there be better Personally Identifiable Information (PII) redaction for data sharing?

Who can offer guidance on what kinds of data practices are ethical and responsible?

Low-Code AI Systems:

The justice community is never going to have large tech, data, or AI working groups within their legal aid or court organization. They are going to need low-code solutions that will let them deploy AI systems, fine-tune them, and maintain them without a huge technical requirement.

Overall, the presentation, Q&A, and workshop all pointed to enthusiasm for responsible innovation in the AI+A2J space. Tech developers, legal experts, and strategists are excited about the opportunity to improve access to justice through AI-driven solutions, and enhance efficiency and effectiveness in legal aid. With more brainstormed ideas for solutions in this space, now it is time to move towards R&D incubation that can help us understand what is feasible and valuable in practice.