Pew Charitable Trusts, which has been engaged in the work dating back to last year, also published a new article elaborating on its new partnerships with the law schools at each institution.
The law schools at Stanford and Suffolk universities have now joined an ongoing effort to make the nation’s non-criminal legal system easier to navigate without lawyers.
From the start of this civil legal system modernization project, which was initiated and spearheaded last year by Pew Charitable Trusts, technology has been key to the plan, which in part seeks to make online legal information portals a better option for users at the state and local levels. The participation of Stanford and Suffolk will help this effort tap into artificial intelligence in this effort.
Pew Charitable Trust published a new article this week detailing its partnership with the academic institutions, titled How Artificial Intelligence Could Improve Access to Legal Information. The article explores both benefits and potential pitfalls of deploying AI in service of these goals. It also describes how the project is using a game it created called Learned Hands to help identify and code tens of thousands of related legal questions as to be recognizable by AI, which could then guide users to answers.
The crux of this is the notion that residents involved in the civil court system often go online to look for answers to their legal questions, and that the information typically found online about this subject is insufficient or difficult to locate. AI can help guide users to the right places, but to do so the machines need to develop a natural language processor (NLP) to help them understand how people talk and, by extension, what kinds of answers they seek. One example in the article relates to AI understanding the definition of “evicted” versus the more commonly used and colloquial “kicked out of my house.”
The teams from Stanford and Suffolk will get funding and support from Pew Charitable Trusts. These teams have collected large numbers of online questions about likely non-criminal legal issues and will now develop data sets that can boost NLPs capable of recognizing the common ways people describe legal issues in online searches.
The Learned Hands game they created is a way to get people to provide the program with data about how they talk. Created by the law school teams, the game is available to be played here, and by spending a few minutes with it, interested parties can help developers get the info they need to build tech that could improve the accessibility of the civil courts system.
The end goal of the project is to give people in the non-criminal court system the ability to navigate the entirety of the legal process from their smartphones or computers, and in the process reducing the burden on both residents and local and state governments.