Jurix 2007 Workshop on Access to Justice: Putting the “i” into wiki


From the very beginning of AI and Law as a research field and  up to the present, access to justice has been a recurrent theme not the least in  the JURIX conferences. Indeed, the promise of socially valuable contributions of this kind  has often been one of  the main selling points for the development of legal expert systems.
In principle, the logic sounds unfaultable: Since costs are the main obstacle to  access to justice, and the main generator of costs are  human experts (lawyers), replacing the human expert by an appropriate advice system should be an obvious way to reduce costs and hence increase access. However, apart from isolated success stories such as splitup and similar web based applications, which are typically confined to very specific legal questions, little of the initial promise has been fulfilled.
A recurrent problem for industrial strength systems that help laypeople with legal problems has been the knowledge acquisition bottleneck: Once a system leaves the confines of an academic project, maintenance  and updating of the necessary knowledge becomes a costly problem, and in some cases relies on the goodwill of the  very same people the system is in competition with.
Recent developments in collaborative software for web 2.0 may offer a solution: success stories such as wikipedia have shown that it is possible to mobilise globally large communities of interested contributors. With is a small cost (in terms of time) for the individual contributor, the result of the coordination of thousands of them is a valuable knowledge repository. Jurispedia is one of several attempts to apply the same underlying model to the field of law. However, while projects such as this can be seen as a practical answer to the problem of access to justice, they face their own shortcomings. Simple putting legal content on the web, even if form of commentaries written for non-lawyers, will be of little use to laypeople who are lacking the relevant knowledge to make sense of this information, and to apply abstract rules to the specifics of their case.
Legal AI and wiki-type large scale net based collaboration therefore seem to be two sides of the same coin, and together they may be a new approach to computer assisted access to justice. To paraphrase Kant: Legal information without intelligent, theory driven user support is blind, but legal AI without large scale legal information is mere intellectual play.
However, so far there has been little interaction between the respective groups of researchers. This workshop hopes to take  a first step in bridging this gap, by bringing together researchers in traditional legal AI and people interested in the use of large web based collaborative projects. The workshop invites in particular contributions to these correlated questions:
  • what contribution can web based collaborative software make to the development of scalable legal expert systems that aim to facilitate access to justice? Projects such as lawunderground offer an ambitious answer to this question which is directly motivated by the question of access to justice. But should we really leave it to the collaborators to contribute not only legal content, but formal representations of law? Can we think of different ways to develop a community of contributors that produce, maintain and update legal knowledge?
  • what contribution can legal AI make to help wiki-type projects of legal knowledge generation, to help them achieve their potential for improving access to justice? Several recurrent research themes in the field of AI and Law could be promising candidates, from information retrieval to education software to visualisation or argumentation support tools. Can intelligent legal information retrieval help laypeople make optimal use of projects such as jurispedia? Are intelligent tutorials and other teaching tools the answer? Or should we think in radically new ways about the interface of AI and text based legal information? Can we use for instance intelligent computing tools to overcome the persistent problem of quality control in open collaborative system? Can experience in legal expert system design help us to identify and correct inconsistencies or mistakes?
  • Access to justice: what type of law? Law does not exist in a vacuum. Jurisprudential schools such as American legal realism or economic analysis of law heighten our awareness that what a citizen in need of advice often requires is more than just an abstract account of the law. They also emphasise the importance of legal roles: advice that is appropriate for a claimant may not be the best advice for the defendant in the same case. Design of suitable net based citizen advice systems have therefore to answer some fundamental philosophical and methodological issues in the design stage: How much extra-legal information is required to give meaningful legal advice? Should support lead the citizen to the “scientifically correct” or the “personally most helpful” answer, what is the relation between them and how does it translate into the design of the wiki environment? Should the distributed expertise of the collaborators simply include experts from other domains, whose contributions can be linked to  the legal information or should the legal information itself make its economic, social or psychological implications explicit? Over the past couple of years,  research in the AI and Law community has shifted away from issues of mere legal interpretation and legal reasoning to  issues of evidence and fact. This too opened up the question of multi-disciplinary knowledge modelling, and the scientific status of legal process and procedure. Can the tentative answers given in this field help more comprehensive wiki-based knowledge repositories for access to justice? Can in turn collaborative environments help legal AI  projects that are primarily interested in computational accounts of reasoning with facts and evidence in  law to incorporate the relevant scientific knowledge?
Call for papers
Short position papers (max. 2 pages) and elaborate research papers (max. 10 pages) can be submitted to the conference organizers. Papers should discuss one of the topics mentioned above or a similar topic. Papers will be subject to review. The deadline for paper submission is November 21. Notification of acceptance will be issued on November 28, or earlier, at the organizers' discretion. Submissions can be sent to e.hoorn@rug.nl. You can use the template available on this website.
The online journal SCRIPT-ed is interested to publish the papers after peer review. A revised version of the paper should be available for review by January 15th. See for editorial guidelines:
Workshop organizers
The workshop is organized by:
Important dates
  • November 21, 2007: Submission deadline
  • November 28, 2007: Notification of acceptance
  • December 15, 2007: Workshop