Online Dispute Resolution A Digital Door to Justice or Pandora's Box? Part 2, 0320 COBJ, Vol. 49, No. 3 Pg. 32
| Author | BY DOUG MCQUISTON AND SHARON STURGES |
| Position | Vol. 49, 3 [Page 32] |
ALTERNATIVE DISPUTE RESOLUTION
BY DOUG MCQUISTON AND SHARON STURGES
This three-part series takes a deep dive into the future of online dispute resolution in Colorado. Part 2 discusses ODR applications that use artificial intelligence to facilitate quick resolution of conflicts.
Part 1 of this article discussed video-conference-based mediation, a form of online dispute resolution (ODR). The next jump in sophistication when using ODR is artificial intelligence (AI)-assisted ODR, which is the focus of this Part 2.
Why Use AI-Assisted ODR?
For conventional mediations, web-based videoconferencing is an excellent solution to the logistical challenges of trying to assemble all participants in one physical location. But conventional and video conference mediation aren’t appropriate for all types of disputes. For example, the amount at stake may be insufficient to justify the cost of a human mediator, even the lower cost of a human mediator who appears via videoconference. Pro se litigants, who commonly appear in small claims, county court, and family law matters, might be reluctant to proceed without counsel at a mediation, and thus not see a conventional mediation as an option. And scheduling a mediation presents the same challenges, whether it occurs in brick and mortar or virtual conference rooms.
AI-assisted ODR offers an efficient, user-friendly dispute resolution solution for such litigants. It offers benefits such as time asymmetry, which allows parties to log in any time they are available, post their position or request, and get a response from any other party or the mediator at their convenience.
The tools discussed here are currently used extensively in Canada, and elsewhere, including in some U.S. state court systems. They are coming to Colorado too. The Colorado courts statewide Office of Dispute Resolution recently obtained a Pew Charitable Trust grant to develop a package of ODR applications that will include AI-assisted ODR. These applications will be designed for use in smaller damages disputes (county court and small claims money judgment matters) and domestic dockets throughout the state. Thus, if you represent commercial or family law clients, you will likely find yourself handling a dispute funneled into one of these tools. And the use of these tools will likely be expanded to other types of disputes within a few years.
“Smart” Systems Guide Litigants
Several centralized, court-sponsored ODR applications are already in commercial and public use or will be on boarded in the near future. Some of the more powerful ODR tools use “artificial narrow intelligence” features, which have user interfaces that apply algorithmic progressions for “smart” question-and-answer dialogue. Like TurboTax® and other software packages, these AI-assisted tools provide easy and secure web login and ask users detailed questions about their dispute, collecting data points about the case along the way. The “smart” part of the tool then uses this data to steer participants toward appropriate procedural tools, display pop-up information guides, and officer forms such as demand letters, response letters, and court documents. The tools even guide negotiations. When the negotiation results in a resolution, the tools assist the litigants in completing the necessary settlement agreements and court dismissal paperwork.
These ODR tools are already in use in British Columbia courts for both domestic and smaller-dollar civil disputes, as discussed below. Several jurisdictions in Australia use these tools extensively with domestic dockets and traffic matters. The tools are commonly designed for pro se litigants, to improve their access to civil justice. But when a pro se litigant sues a party represented by counsel, the represented defendant can involve his or her counsel in the online tool as they would in court.
The more powerful AI-assisted ODR tools use algorithmic data mining of all disputes in their system, completely anonymously. They gather data on offer and demand progressions, case settlement ranges, and court judgment ranges in all of the disputes that use the tool, based on the facts input by the users. They “learn” from this data to determine how typical disputes with similar fact patterns are being resolved.
The tools solicit input from each...
To continue reading
Request your trial