{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T22:53:36Z","timestamp":1767135216110,"version":"build-2238731810"},"reference-count":13,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T00:00:00Z","timestamp":1648684800000},"content-version":"vor","delay-in-days":30,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["AI Magazine"],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>To craft effective public policy, modern governments must gather and analyze data on both the performance of their public functions and the responses by the public. Federal administrative agencies such as the Patent Office and Centers for Disease Control routinely do this, as does the United States Congress. More importantly, they make such data freely accessible. Within the United States government, however, the judicial branch is a conspicuous outlier. In theory, federal court records could be used to evaluate the efficiency and fairness of the justice system. In practice, court records are effectively out of reach because they sit behind a government paywall. This financial barrier, along with an equally important myriad of technical obstacles, have forestalled the development of AI\u2010driven analysis that could enable a systematic understanding and evaluation of the work of the courts.<\/jats:p>\n                  <jats:p>The Systematic Content Analysis of Litigation EventS Open Knowledge Network (SCALES OKN) seeks to address this situation by transforming the transparency and accessibility of court records. The SCALES OKN will potentiate the development of new AI solutions that will benefit the judiciary, legal scholars, and the public. In this article, we outline some of key financial, technical, and policy challenges to developing novel AI solutions.<\/jats:p>","DOI":"10.1002\/aaai.12039","type":"journal-article","created":{"date-parts":[[2022,5,9]],"date-time":"2022-05-09T08:42:36Z","timestamp":1652085756000},"page":"69-74","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["The Promise of AI in an Open Justice System"],"prefix":"10.1002","volume":"43","author":[{"given":"Adam R","family":"Pah","sequence":"first","affiliation":[{"name":"Kellogg School of Management Northwestern University  Evanston Illinois USA"}]},{"given":"David L","family":"Schwartz","sequence":"additional","affiliation":[{"name":"Pritzker School of Law Northwestern University  Chicago Illinois USA"}]},{"given":"Sarath","family":"Sanga","sequence":"additional","affiliation":[{"name":"Pritzker School of Law Northwestern University  Chicago Illinois USA"}]},{"given":"Charlotte S","family":"Alexander","sequence":"additional","affiliation":[{"name":"Robinson College of Business Georgia State University  Atlanta Georgia USA"}]},{"given":"Kristian J","family":"Hammond","sequence":"additional","affiliation":[{"name":"McCormick School of Engineering Northwestern University  Evanston Illinois USA"}]},{"given":"Lu\u00eds A.N.","family":"Amaral","sequence":"additional","affiliation":[{"name":"McCormick School of Engineering Northwestern University  Evanston Illinois USA"}]},{"name":"SCALES OKN Consortium","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2022,3,31]]},"reference":[{"issue":"1","key":"e_1_2_8_2_1","first-page":"37","article-title":"Making Doctrinal Work More Rigorous: Lessons from Systematic Reviews","volume":"84","author":"Baude W.","year":"2017","journal-title":"The University of Chicago Law Review"},{"key":"e_1_2_8_3_1","unstructured":"Bielen A. 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M.\u2010W.Chang K.Lee andK.Toutanova.2019. \u201cBERT: Pre\u2010training of Deep Bidirectional Transformers for Language Understanding.\u201dhttp:\/\/arxiv.org\/abs\/1810.04805"},{"key":"e_1_2_8_5_1","unstructured":"\u201cFederal Judicial Caseload Statistics.\u201d2018.https:\/\/www.uscourts.gov\/statistics\u2010reports\/federal\u2010judicial\u2010caseload\u2010statistics\u20102018"},{"issue":"6","key":"e_1_2_8_6_1","first-page":"1478","article-title":"Pleading Poverty in Federal Court","volume":"128","author":"Hammond A.","journal-title":"The Yale Law Journal"},{"key":"e_1_2_8_7_1","first-page":"87","volume-title":"Positioning and Power in Academic Publishing: Players, Agents and Agendas","author":"Kluyver T.","year":"2016"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.aay3005"},{"key":"e_1_2_8_9_1","unstructured":"Montani I. 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F.Adler M.Sterbentz A.Pah D.Schwartz C.Barrie A.Einarsson andK.Hammond.2021. \u201cFrom Data to Information: Automating Data Science to Explore the U.S. Court System.\u201dIn ICAIL '21: Eighteenth International Conference for Artificial Intelligence and Law.https:\/\/doi.org\/10.1145\/3462757.3466100","DOI":"10.1145\/3462757.3466100"},{"key":"e_1_2_8_13_1","unstructured":"SCALES OKN Consortium.2021. \u201cscales\u2010okn\/Research\u2010Materials: Sealing Analysis.\u201dhttps:\/\/doi.org\/10.5281\/zenodo.5056441"},{"key":"e_1_2_8_14_1","doi-asserted-by":"crossref","unstructured":"Wolf T. L.Debut V.Sanh J.Chaumond C.Delangue A.Moi P.Cistac T.Rault R.Louf M.Funtowicz J.Davison S.Shleifer P.vonPlaten C.Ma Y.Jernite J.Plu C.Xu T. L.Scao S.Gugger M.Drame Q.Lhoest andA. 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