Suffolk University Law School’s Legal Innovation & Technology (LIT) Lab has teamed up with Stanford’s Legal Design Lab to build a dataset of roughly 75,000 labeled questions commonly asked by ordinary consumers. The task might sound mundane, but it’s critical in helping to make online legal help portals more efficient at assisting users nationwide who seek online assistance with their legal problems. The effort was highlighted in the ABA Journal’s May 22 article, “Want to improve AI for law? Let's talk about public data and collaboration.”

The publication spoke with David Colarusso, the director of the LIT Lab, who explained that online searches for legal advice can be challenging. When consumers seek out legal advice on a help portal, the information is generally served up to them as part of a wide subject area of the law, say family law, rather than focusing in on a specific question: “What steps can I take if my spouse is making it difficult for me to see my child on agreed upon visitation dates?”

Colarusso said the labs’ labeled dataset will make it possible to train machine learning algorithms to find very specific and more useful content for consumers rather than general content areas. The LIT Lab’s effort is designed to help address the justice gap, making it easier for people who can’t afford attorneys to get the basic information they need to defend themselves. The project is currently seeking help from volunteer attorneys.

ABA Journal explained that “large, available datasets like the one being created by Suffolk and Stanford would lower the cost of entry for new companies and researchers in this space and embolden exploration of these important issues. These datasets would create a ripple effect through the profession that building a single, proprietary dataset does not.”