Artificial intelligence can be particularly helpful for alternative dispute resolution, say lawyers, as long as people are mindful of the technology’s limitations.
Artificial intelligence can be particularly helpful for alternative dispute resolution, say lawyers, as long as people are mindful of the technology’s limitations.
Marvin Huberman, president of the Alternative Dispute Resolution Institute of Ontario, says artificial intelligence could do more than just analyze data for patterns.
“Artificial intelligence, a relational agent, can contribute in a very significant way to alternative dispute resolution and problem solving either by being intelligent or behaving intelligently,” he says.
Huberman says he does not think artificial intelligence will completely replace human mediators or arbitrators. But he thinks artificial intelligence could be used at the beginning of a mediation process to answer questions about how the mediation process will unfold. Huberman says a robotic machine could repeat information without growing impatient, like human mediators might. People may also be more comfortable sharing details about sensitive events to a robot than to a person, he says.
“It may be better for some people to relay that information to a non-judgemental avatar or a robot or an artificial intelligence device,” says Huberman.
William Horton, an independent commercial arbitrator and lawyer in Toronto, says arbitrations are shorter than litigations, and this makes artificial intelligence particularly helpful when cases involve lots of documents. Arbitrators have less time to read the documents. Horton moderated a panel discussion on uses of technology in arbitration at the Toronto Commercial Arbitration Society's annual general meeting on May 28.
“In arbitration, we're typically dealing with very short deadlines,” Horton says.
“The document production process in litigation can go on for two years without anyone batting an eye or thinking there's anything unusual about that. The whole discovery process, including examinations for discovery might go on for several years in some commercial cases.”
That's not the case in arbitration, says Horton.
“Typically, even in big high-value arbitrations, we're running procedures that go from six months to a year,” he says. “If there is an effective method for reviewing [large amounts of] documents for relevant information that could take place in a matter of weeks or days as opposed to years, that's of great interest.”
Benjamin Alarie is co-founder and CEO of Blue J Legal, a Toronto-based company that produces research tools that lawyers can use in tax or employment situations. Lawyers answer questions about the particular situation, and then the system provides a prediction about the situation based on a collection of legal information, including cases and statutes.
“If you know what would likely happen if a dispute would go to court, then that would likely inform the terms to which you would be likely to go to a settlement,” says Alarie, who is also a member of the Ontario bar.
The company created Tax Foresight, which focuses on tax law, and Employment Foresight, which focuses on employment law.
“What the two areas share in common is that they both affect virtually every person in society,” Alarie says, noting that almost everyone pays taxes. “There's a huge potential group of beneficiaries of these tools.”
The company has around 60 employees, almost half of which are legal researchers who collect and curate data that data scientists than use to create datasets, says Alarie.
“The better the data quality is, the easier is the job of the data scientist,” says Alarie.
Yet lawyers still need to be aware of the limits of artificial intelligence, says one lawyer. Omar Ha-Redeye has completed courses in coding and predictive analytics so he can better understand how artificial intelligence works and what its capabilities are.
“At its best, artificial intelligence identifies patterns that would not be readily ascertainable to the human mind. That's what we're trying to find,” says Ha-Redeye, who practises with Fleet Street Legal in Toronto.
Technology has limits, says Ha-Redeye.
“Sometimes there is an over-selling of the capabilities,” he says.
Alarie, for example, says Blue J Legal aims to be very conscious of potential for bias in its products, noting the company has an ethics committee.
“Bias is a potential for any legal system,” he says, adding people raise concerns about bias with any emerging technology.
“Right now, we have various safeguards against bias by having trial courts and appellant courts and increasingly large panels of judges hearing appeals as you kind of rise up through the ranks of the litigation process,” Alarie says.
Machine learning, he says, can potential “scrub away” the individual biases of a particular judge.
“One way of thinking about what the system's doing is it's really predicting, based on all of the existing cases that the system is exposed to and trained on, what would the entire audience of past judges do in a particular case. It's really minimizing the idiosyncratic bias that you might have with any particular case, and basically what you're left with is systemic bias or the general approach of the courts as a whole to a particular issue,” Alarie says.
Alarie says products like the ones his company develops could alleviate access to justice concerns, because, in his view, technological delays contribute to people struggling to have their legal needs met by the legal profession.
“It's really going to allow greater transparency in the law, better access to justice, more reliable, quicker legal information,” he says.
“People will know where they stand legally, and disputes will resolve more quickly. It will really be through these technologies that we really address the serious issues that we have surrounding the access to justice and affordability."
