Open AccessThe Promise of AI in an Open Justice System
Author(s) -
Adam R. Pah,
David A. Schwartz,
Sarath Sanga,
Charlotte Alexander,
Kristian J. Hammond,
Luı́s A. Nunes Amaral,
SCALES OKN Consortium
Publication year - 2022
Publication title -
the ai magazine/ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v43i1.19127
Subject(s) - transparency (behavior) , craft , government (linguistics) , political science , open government , public administration , economic justice , work (physics) , business , public relations , law and economics , engineering , law , sociology , mechanical engineering , linguistics , philosophy , archaeology , history
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-driven analysis that could enable a systematic understanding and evaluation of the work of the courts.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.