Peter A Allard School of Law

Using Artificial Intelligence to Enhance Access to Justice in Online Dispute Resolution – How Can We Help Self Represented Litigants?

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Legal technology holds promise for providing access to justice (“A2J”) through the use of online dispute resolution (“ODR”) to Self-Represented Litigants (SRLs). This is because ODR uses technology to enable online claim diagnosis, negotiation, and mediation without the time, money, and stress of traditional court processes. Indeed, courts are now moving traffic ticket, landlord-tenant, personal injury, debt collection, and even divorce claims online.

The hope is that legal tech such as online triage and dispute resolution systems will provide means for obtaining remedies for SRLs and those who cannot otherwise afford traditional litigation. These online processes seem focused mainly on case management and communication, neglecting the need for more imaginative and innovative uses of technology.

We propose a six-module system for ODR programs and identify gaps in development where new technologies are needed to advance A2J. Indeed, there is great room for the development of Artificial Intelligence and data analytics to assist SRLs and others in pursuit of remedies and justice

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John Zeleznikow
John Zeleznikow

John Zeleznikow is Professor of Law and Technology at La Trobe University in Melbourne Australia.  In his Split-Up system of the 1990s he pioneered the use of machine learning to support legal decision making.  The application area was the distribution of property in Australian Family Law.  He followed this up with the use of game theory to support trade-offs in legal disputes. He has written 4 books and 102 refereed journal articles, received over $C8 million in research grant funding and successfully supervised 20 PHD students. He has a H index of 37, with 4476 citations.

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