Online dispute resolution is a growing field and is already in use when domain names are contested.
Online dispute resolution is a growing field and is already in use when domain names are contested. Lawyers and alternative dispute resolution professionals note that while ODR can work for some kinds of disputes, it lacks the personal touch that ADR professionals can bring to the table.
“Given the way we do things in an online world, I do believe this kind of process is going to be the way of the future, but I think it will be limited to certain types of disputes,” says Randy Sutton, partner at Norton Rose Fulbright Canada LLP in Toronto, practising in the area of dispute resolution.
“One of the benefits of ADR is the parties coming together to design what process they can best use to resolve their dispute.”
Sutton says that because domain names are already an online issue, an ODR process makes natural sense.
For other groups, including seniors, it would make less sense to use an ODR process. Another example is the British Columbia Civil Resolution Tribunal, which takes some of the smaller claims and puts them through an online process to get a decision, similar to domain name process, but it is more consumer-focused and broader as to what it applies.
“Technology is changing the practice, and any time there’s an opportunity to create efficiencies and access to justice, we as a profession need to be aware of it,” says Samaneh Hosseini, partner with Stikeman Elliott LLP in Toronto, who is part of the litigation and dispute resolution group.
“It certainly can be very effective for certain types of cases.”
Sutton says that ODR can work for domain name disputes because there aren’t a lot of credibility issues or emotions involved, as opposed to larger or more complicated cases, which need a neutral third party or arbitrator to listen to the parties, to understand their positions and engage them in a dialogue.
“I still think that process is ultimately needed for a lot of cases to settle,” says Sutton.
As more automation, including deep learning tools, become available in law, there is a sense that this may be where some forms of ODR may be headed.
“There’s simply an ability for simple questions to be answered by automation, by artificial intelligence, but I think one of the challenges when you’re looking at ADR or dispute resolution [is] there is a legal component, but there is also that emotional, human component,” says Sutton.
“With dispute, you need someone to understand the legal side, but you still have to have that emotional mediation approach.
“Your legal position may be x, but your emotional position in terms of settlement may be y, and someone needs to bridge that gap,” adds Sutton. “That’s where the human element comes in.”
Sutton says more complicated cases, where credibility issues are at play or where differing valuations may be in play, are less suited for an automated process, as are personal injury cases.
“I don’t think all cases are going to be suitable,” says Hosseini.
“Cases involving e-commerce or small financial claims are probably best resolved through ODR, and certainly it would be important to bring greater access to justice through those resolution mechanisms.”
Hosseini says that, while there may be ODR tools that could build efficiencies, such as video conferencing being used right now or online filing of mediation materials or pre-mediation work, large or more complex cases still require a human element.
“Clients need to interact with the mediator to build trust as a first step,” says Hosseini.
“Sometimes, clients just want an opportunity to be heard — there’s an emotional element that you don’t get through an ODR process.”
Other ADR professionals see a further move toward AI in law.
“ODR historically has been things like making offers to a virtual mediator, and if there’s an overlap they can make a deal,” says Alan Stitt, president of ADR Chambers in Toronto and a former litigator.
“It’s a really simplistic, purely online process.”
Stitt says that the models put forward by the company doing computer deep learning to research tax law in order to predict the results of future cases has shown to be quite accurate.
“If we really are stepping back and saying [that] 50 years from now, there’s going be a heck of a lot more of that,” says Stitt.
The real challenge according to psychologists, says Stitt, is that people are unwilling to assume that their case falls within the established norm and believe that they are an exception.
“In the short term, I suspect there will be a lack of willingness to accept the result that a computer tells you,” says Stitt.
“If it’s analytically correct that you can predict these cases really well, there are enormous cost savings to litigants and cost savings to litigators in the long term.”
