At the end of last year, I had the chance to do a Q+A with Kumar Garg, the President of Renaissance Philanthropy, where I’m the Court Innovation Fellow. In this role, I’m leading the development of a philanthropic fund focused on building the field of court innovation. Below is a selection of the conversation explaining the role philanthropy can have in the development of rights-protecting AI in American courts. Please visit the RenPhil website(This link opens in a new tab) to read the whole interview.

KG: Why did you join Renaissance Philanthropy to design this work, and what role can philanthropy play in shaping how technology and AI enter the courts?

JT: The chokepoints I mentioned above are created by limitations in the court techstack, court staff training, and research. Scalable technology, modular trainings, and spurring novel research are three things that philanthropy is adept at catalyzing. However, philanthropy has largely been absent from the courts, leaving a core American institution in disrepair.

Specifically, there’s a need for increased technical sophistication across states that a fund like our can support. For example, every court in the country needs a case management system – it’s the digital backend that makes a court work. However, there’s no agreed standard to what a CMS should cost, leaving courts in the dark when negotiating with private vendors. If wasted money wasn’t enough, when new CMS roll out(This link opens in a new tab) they are often followed by false arrests and people being held in custody longer than their jail sentence. Philanthropy can spark the research into what a CMS should cost and how to prevent software glitches from sending people to jail.

Teaming up with Renaissance provides an opportunity to work with brilliant minds across science, technology, and philanthropy to refine and execute a more impactful vision. Since starting here, I’ve been challenged to think bigger and more critically about how to deploy resources that build the court innovation field and set the agenda for a still developing space. While building on my previous work, the team is uniquely positioned to challenge assumptions and share lessons from other fields–all leading to a more thoughtful and complete path forward.

KG: Courts are processing millions of cases a year and facing an “AI tsunami.” How do you think these technologies will reshape the front door of American democracy, and what’s at stake if courts don’t get ahead of it?

JT: This isn’t trouble ahead, the tsunami is here now. A few weeks ago, I wrote about a bill in Wisconsin that would replace human court translators with AI software. As I outlined in the Milwaukee Journal Sentinel(This link opens in a new tab), the state will regret this bill becoming law, because the technology isn’t ready for high-stakes situations like the courts. This is for two reasons. First, most languages are “low-resource” meaning there isn’t a lot of content online in a language like Hmong, Wisconsin’s third most spoken language, which limits the ability to train an AI system to make accurate translations. Second, even a high-resource language like Spanish, which has lots of online content to train AI on, mistranslates legal terms. “Due date” becomes “date to give birth”, and the pronoun “su” (either “your”, “his”, “her”, or “their”) can be mistranslated, sowing confusion over property ownership or legal responsibility. These are not harmless errors, and if legislators in Wisconsin have their way the courts will have to figure out how to get to the facts of the case without a trustworthy translation.

This is just one example of the tsunami that’s already here. In other instances, court watchers are seeing an uptick of debt cases in state courts, which they believe is aided by AI(This link opens in a new tab). It’s already well documented(This link opens in a new tab) that debt claims are often low quality and depend on the defendant not showing up to court to win. AI has the potential to supercharge this predatory practice. Courts are reacting by building automated AI review tools to ensure that debt claims are credible before ruling. While this is a welcome innovation, we lack the tools, like benchmarks, to know if these review tools are accurate or contain hidden biases.

These two examples illustrate what is at stake for courts getting this moment right. Courts provide a process for fact finding and getting at the truth of a legal matter. To adopt AI translation services too early or to rely on unvalidated software to determine case outcomes risks the public’s trust. With nearly 70 million cases a year, courts are one of the most common touch points for the public and our government, getting it wrong there undercuts trust in our entire democratic system.