The Promise of AI in an Open Justice System
DOI:
https://doi.org/10.1002/aaai.12039Abstract
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.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 AI Magazine
This work is licensed under a Creative Commons Attribution 4.0 International License.
- The author(s) warrants that they are the sole author and owner of the copyright in the above article/paper, except for those portions shown to be in quotations; that the article/paper is original throughout; and that the undersigned right to make the grants set forth above is complete and unencumbered.
- The author(s) agree that if anyone brings any claim or action alleging facts that, if true, constitute a breach of any of the foregoing warranties, the author(s) will hold harmless and indemnify AAAI, their grantees, their licensees, and their distributors against any liability, whether under judgment, decree, or compromise, and any legal fees and expenses arising out of that claim or actions, and the undersigned will cooperate fully in any defense AAAI may make to such claim or action. Moreover, the undersigned agrees to cooperate in any claim or other action seeking to protect or enforce any right the undersigned has granted to AAAI in the article/paper. If any such claim or action fails because of facts that constitute a breach of any of the foregoing warranties, the undersigned agrees to reimburse whomever brings such claim or action for expenses and attorneys’ fees incurred therein.
- Author(s) retain all proprietary rights other than copyright (such as patent rights).
- Author(s) may make personal reuse of all or portions of the above article/paper in other works of their own authorship.
- Author(s) may reproduce, or have reproduced, their article/paper for the author’s personal use, or for company use provided that original work is property cited, and that the copies are not used in a way that implies AAAI endorsement of a product or service of an employer, and that the copies per se are not offered for sale. The foregoing right shall not permit the posting of the article/paper in electronic or digital form on any computer network, except by the author or the author’s employer, and then only on the author’s or the employer’s own web page or ftp site. Such web page or ftp site, in addition to the aforementioned requirements of this Paragraph, must provide an electronic reference or link back to the AAAI electronic server, and shall not post other AAAI copyrighted materials not of the author’s or the employer’s creation (including tables of contents with links to other papers) without AAAI’s written permission.
- Author(s) may make limited distribution of all or portions of their article/paper prior to publication.
- In the case of work performed under U.S. Government contract, AAAI grants the U.S. Government royalty-free permission to reproduce all or portions of the above article/paper, and to authorize others to do so, for U.S. Government purposes.
- In the event the above article/paper is not accepted and published by AAAI, or is withdrawn by the author(s) before acceptance by AAAI, this agreement becomes null and void.