{"671554":{"#nid":"671554","#data":{"type":"news","title":"Charlotte Alexander Uses NSF Grants to Create an AI-Powered, Publicly Accessible Court Data Platform","body":[{"value":"\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cdiv\u003E\r\n\u003Cp\u003EImagine accessing court documents and data, both civil and criminal, in the state of Georgia through a free central repository. Now imagine this access across the entire U.S. court system.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.scheller.gatech.edu\/directory\/faculty\/alexander\/index.html\u0022 rel=\u0022noopener\u0022 target=\u0022_blank\u0022\u003ECharlotte Alexander\u003C\/a\u003E, professor of Law and Ethics at the Georgia Tech Scheller College of Business, is working on a project that uses AI to mine the text of court records. Her work includes pulling key pieces of information out of court documents and making it freely available to attorneys, judges, prosecutors, criminal defendants, civil litigants, journalists, policymakers, researchers, and any member of the public.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECurrently, court records are stored in systems that are expensive, fragmented, outdated, and hard to navigate. Alexander sees a lack of good data as a key problem impeding court reform efforts. Better data, she says, \u0022would shed light on questions around efficiency and time of action, how long things take, and why there are delays. But it also raises big, heavy, substantive questions about bias and who wins and who loses. Does our legal system actually deliver justice, and if so, to whom?\u0022 said Alexander.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHer work, funded primarily through National Science Foundation (NSF) grants, is multi-faceted. She and a team of researchers received an initial grant from the NSF\u2019s \u003Ca href=\u0022https:\/\/www.youtube.com\/watch?v=3XK1icNpevI\u0022\u003EConvergence Accelerator Project\u003C\/a\u003E, which was designed to fund efforts to create new sources of data and then make that data publicly available.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWorking on the Federal Level\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThis initial work with colleagues at Georgia State University, Northwestern University, University of Richmond, and the University of Texas - Austin focused on the federal courts.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0022When we started all of this on the federal level, we assembled court records from two full years of all federal cases filed, so everything filed in 2016 and 2017, we downloaded four years later. So, by 2020 and 2021, most of those cases had concluded. Now, we have this \u003Ca href=\u0022https:\/\/scales-okn.org\/\u0022 rel=\u0022noopener\u0022 target=\u0022_blank\u0022\u003Ebig snapshot of federal litigation\u003C\/a\u003E, including comprehensive data on the progress, pathways, and outcomes of cases that we built using machine and deep learning tools on all those documents,\u0022 said Alexander.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFor example, Alexander provided a small glimpse into how this system might improve court operations. When plaintiffs file a civil case in federal court, they are responsible for a filing fee of $400. The fee can be waived, but individual judges make fee waiver decisions, developing their own separate sets of rules.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe research team\u0027s data extracted from court records showed that some judges granted more than eighty percent of waiver requests, whereas others granted fewer than twenty percent. (\u003Ca href=\u0022https:\/\/www.science.org\/doi\/10.1126\/science.aba6914\u0022 rel=\u0022noopener\u0022 target=\u0022_blank\u0022\u003E\u003Cspan\u003Ehttps:\/\/www.science.org\/doi\/10.1126\/science.aba6914\u003C\/span\u003E\u003C\/a\u003E).\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn other words, whether a litigant received a fee waiver depended on the luck of the draw \u2013 on the judge to whom the case was randomly assigned. This analysis has prompted courts to reconsider their fee waiver procedures to ensure greater consistency.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0022We found in our conversations with judges that there\u0027s a lot of appetite for this type of system-level knowledge. And by that, I mean, \u0027I know how I manage the cases in my courtroom, but I don\u0027t really have a good way to know how other judges handle similar cases,\u0027\u0022 she said.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EWorking on the State Level\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFast forward a few years, and Alexander is currently working to extend her work beyond the federal courts with funding from the NSF\u2019s \u003Ca href=\u0022https:\/\/new.nsf.gov\/tip\/updates\/nsf-invests-first-ever-prototype-open-knowledge-network\u0022 rel=\u0022noopener\u0022 target=\u0022_blank\u0022\u003EPrototype Open Knowledge Network (Proto-OKN)\u003C\/a\u003E program, which supports the development of \u0022an interconnected network of knowledge graphs supporting a very broad range of application domains.\u0022\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0022We\u0027ve got all this data that we generated, and now we want to flesh it out further, and then feed it into this larger technical apparatus that the NSF is helping fund, which is the knowledge graph infrastructure,\u0022 she said. \u0022The NSF wants to map different pockets of knowledge so we might connect, for example, census tract level poverty data to different measures of economic development and economic activity to court data using the concept of a knowledge graph to organize all of these nodes.\u0022\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAlexander and her collaborators received a $1.5 million grant to continue their work on court data access, but this time, on the state level. They are particularly interested in criminal case data from the state courts because, as she puts it, \u0022most criminal prosecutions in the U.S. happen at the state level, not the federal level.\u0022\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThey\u0027re focusing on two initial sites: Georgia, beginning with Fulton and Clayton Counties, and Washington State. Using their experience in these two states, they hope to add data from other states and eventually build out a full picture of both criminal and civil litigation on both the state and federal levels.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAI and Machine Learning\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWith AI and machine learning, Alexander and her colleagues can identify and create results from their data more quickly than they would have even five years ago.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0022In any case, civil or criminal, in either state or federal court, the court generates a docket sheet, which is a chronological list of events in the case. Descriptions can be very different using very different language, even if they\u0027re talking about the same underlying event,\u201d she explained. \u201cThis variation in how court events are recorded makes it difficult to get a system-level view. So, we\u0027ve used AI, particularly deep learning using large language models to train a model or a set of models to recognize all the different ways litigation events show up.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBecause her research reaches many disciplines, she plans to work with collaborators across Tech. She sees value in bringing in students from the Scheller College of Business and other schools including the College of Computing, Ivan Allen College of Liberal Arts, and \u003Ca href=\u0022https:\/\/www.vip.gatech.edu\/\u0022 rel=\u0022noopener\u0022 target=\u0022_blank\u0022\u003EVertically Integrated Projects\u003C\/a\u003E.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0022If we solve the data problem, we\u0027re better equipped to attack the procedural and substantive problems around how the courts actually operate. What\u0027s exciting is the methodological advances in computer science and natural language processing that have cracked wide open the types of questions that are now answerable, which then allows us to change society for the better,\u0022 said Alexander.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDuring the Fall 2023 semester, Alexander is on a Fulbright scholarship in Santo Domingo, Dominican Republic until December to study their digital transformation efforts within the court system and to explore using data to focus on diagnosing problems and creating more efficiency and transparency.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0022A court is an organization and systems-level, organizational thinking about courts is not confined to the U.S. We can start to draw connections and collaborations across international boundaries, which I think is pretty exciting,\u0022 she said.\u003C\/p\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n\u003C\/div\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ECharlotte Alexander, professor of Law and Ethics at the Georgia Tech Scheller College of Business, is working on a project funded by the National Science Foundation, to make federal and state court records available to attorneys, judges, prosecutors, criminal defendants, civil litigants, journalists, policymakers, researchers, and the public using AI and machine learning. The project is part of a larger NSF project called the Prototype Open Knowledge Network (Proto-OKN).\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Charlotte Alexander, professor of Law and Ethics, is working with a National Science Foundation grant to centralize U.S. federal and state court data for public access using AI and language models."}],"uid":"28082","created_gmt":"2023-12-13 15:53:32","changed_gmt":"2023-12-13 20:16:06","author":"Lorrie Burroughs","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2023-12-07T00:00:00-05:00","iso_date":"2023-12-07T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"hg_media":{"672570":{"id":"672570","type":"image","title":"Charlotte Alexander","body":null,"created":"1702481055","gmt_created":"2023-12-13 15:24:15","changed":"1702481123","gmt_changed":"2023-12-13 15:25:23","alt":"Headshot of Charlotte Alexander","file":{"fid":"255838","name":"charlotte-alexander_0.jpg","image_path":"\/sites\/default\/files\/2023\/12\/13\/charlotte-alexander_0.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2023\/12\/13\/charlotte-alexander_0.jpg","mime":"image\/jpeg","size":70176,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2023\/12\/13\/charlotte-alexander_0.jpg?itok=OTnh09kj"}}},"media_ids":["672570"],"related_links":[{"url":"https:\/\/new.nsf.gov\/tip\/updates\/nsf-invests-first-ever-prototype-open-knowledge-network","title":"Prototype Open Knowledge Network (Proto-OKN) program"}],"groups":[{"id":"1274","name":"Scheller College of Business"}],"categories":[{"id":"135","name":"Research"}],"keywords":[{"id":"114801","name":"Law and Ethics Program"},{"id":"187812","name":"artificial intelligence (AI)"},{"id":"103851","name":"criminal justice"},{"id":"187915","name":"go-researchnews"}],"core_research_areas":[{"id":"39511","name":"Public Service, Leadership, and Policy"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003ELorrie Burroughs\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}