In brief - As digitisation of legal services evolves, litigants will need to adapt
The idea of a litigator brings to mind images of Daniel Kaffee and Atticus Finch (or maybe even Elle Woods) dexterously defending the interests of their clients.
While some litigation may still reflect such nostalgia, the introduction of online courts has largely substituted collegial argument before the Honourable court with a series of drop down menus and 2.00pm cut off times.
Litigants may feel separated from their opponents and decision makers, but the OLC (online court) has by no means supplanted the dispute resolution process. In this article, we consider how the rise of ODR (online dispute resolution) has affected other jurisdictions and how it will likely affect practice at home.
Online dispute resolution at large
ODR has been present on a completely automated level for some time.
Various online merchants, including eBay and Alibaba, have AI (artificial intelligence) keeping the wheels of justice turning in relation to minor customer disputes.
As early as March 2015, in Zhejiang, China, the highest local court piloted an online court designed to resolve disputes in e-commerce, with a view to facilitating resolutions "as convenient as online shopping". China is widely implementing digitalisation to increase case-handling efficacy within its expansive court system using both AI and technological outfits, including blockchain and the backing of cloud computing. This includes a mobile based court, housed on prolific social media platform WeChat. The platform has already handled more than three million proceedings since its introduction in March 2019.
While technically the alternative dispute resolution system on online merchant platforms is a modified form of arbitral process agreed by a clickwrap contract entered into on signing up as a member, such systems appear to have been relatively effective at dealing with low level online disputes (much like the medieval law merchant developed to resolve disputes quickly and practically between people attending at markets and fairs from different lands speaking different languages, similar to the informal "legal" systems developed by pirates in the 17th century to divide captured loot).
In British Columbia, the CRT (Civil Resolutions Tribunal) has been introduced in an effort to relieve pressure on the higher courts by filtering out a significant volume of the smaller disputes.
The CRT represents a free dispute resolution tool which requires the parties to engage in mediation at first instance, prior to progressing to commence proceedings. Mediation fails in only a reported two percent of cases. Litigated claims are almost entirely dealt with on the papers through the CRT, though the parties may request an oral hearing via telephone or video link.
Other jurisdictions, including the UK, have been encouraged by the success of the CRT and have pledged resources to developing applicable ODR platforms to facilitate a much needed alleviation on the stressed court system.
UK policy advocates have foreshadowed online dispute resolution clauses in smart contracts, particularly in financial services.
Smart contracts are designed to enable transactions and agreements to be effected between disparate, often anonymous entities, without needing a central authority, or, presently; an external enforcement mechanism.
At the other end of the spectrum, a team of academics have developed a bot fluent in AI that is apparently capable of predicting judgments made in the European Court of Human Rights with a (fairly respectable) 79% accuracy rate.
Quite what the utility of this bot in the real world might be remains to be seen, but the benefit of any advanced form of AI is that it intuits both its successes and failures and adapts accordingly via an algorithmic iterative learning process.
Online dispute resolution closer to home
Legal AI, the Voldemort for some in the legal world, is likely a way off from being implemented in Australian ODR.
However, there are promising applications of AI in certain areas of law, particularly those that involve a tangible prediction task for which there is a large volume of data available.
An example of this is the algorithm developed by Kleinberg et al, which was able to predict which bail applicants were likely to commit a crime upon release. When the AI based application was set to the same release rate as the judges, the algorithm's choices of applicants to release on bail committed 24.7% fewer crimes than those selected by the judges. The computer program only relied on the defendants' age and charges in making its judgment, while the judges engaged with the defendants in open court.
It should be noted that AI based criminal sentencing is the subject of significant human rights concerns in the UK and the US and it is unlikely that the Australian legal system will adopt it (especially in light of the political issues relating to apparent mistakes in the Australian government's AI based collection of alleged overpaid welfare), but in commercial law things are likely to be quite different.
The Federal Court of Australia has produced a machine learning concept, reliant on AI, designed to aid parties to divide assets and liabilities following a separation.
Such a division is usually debated at length (and cost) by family lawyers, however, the Federal Court is testing with what it has named the "FCA Consent Order AI Application" to assist parties to determine a more accurate split likely to obtain the Court's approval. The costs reductions inherent will likely make this attractive to parties.
The current developments in AI are aimed at removing task-based functions of the court and the judiciary, rather than replacing the judicial function.
While we do not anticipate that we will be beholden to Judge Dredd any time in the immediate future, the digitisation of the legal function has started to infiltrate our systems and the way in which we conduct dispute resolution. Litigants are not merely obliged, but incentivised to adapt and engage with the new structure.
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