It is said that knowledge is power. When you consider that knowledge is essentially data given context, it’s no surprise that data collection and machine learning are among the top priorities for some of the world’s leading tech innovators, as well as businesses around the world.
Set against this technological revolution backdrop is the legal sector – specifically disputes resolution – which has long been a playground for disruptive innovation.
What is changing in dispute resolution?
A lot is changing and continues to do so at a remarkable pace. Across many law-related services, including litigation and dispute resolution, we now have practice management systems that have become a lot more intuitive. Together with qualitative contract review, IP management, e-discovery, and much more, they have all been driven by the power of big data, plus different AI techniques.
These new technologies have led to many efficiencies, especially when it comes to costs and time.
The reason for this is that the technology we have access to today is capable of rapidly aggregating and processing vast volumes of data in various forms, helping to make database-driven relational decisions based on simple analysis and hard facts. In time, it would not be altogether surprising to see automation of most human tasks – such is the power of the data potentially available.
Indeed, it certainly seems to be proving effective in solving human problems, because while this change has created enormous potential in nearly all sectors – and society at large – it is of particular use and interest to dispute resolution and arbitration.
For example; Dispute Resolution Data, an American start-up, collates case data from several arbitral institutions such as the ICDR, ICC and CEDR, providing detailed “insight through historic and current geographic as well as case-type reports on dispute resolution claims, durations and processes” – in their own words.
At the moment, the information collected is processed in a relatively simple manner. The data covers industry type, the amount in the claim, location, duration, cost and macro outcomes, such as ‘settled’, ‘withdrawn’ or ‘final award given’. It then provides a trend analysis tool which businesses can use to decide the when, where, whether and how of arbitration. With such volumes of data at their disposal, they can make confident, clear-eyed decisions based on a tangible precedent.
We have seen intelligent solutions with Arbitrator Intelligence and Jur, too.
Together with intelligent practice management software, the potential for big data to be a disruptor in the world of arbitration and dispute resolution is a lot larger than anyone ever anticipated.
How can these changes benefit practitioners and clients?
When we think about data analytics and AI tools in the context of dispute resolution – and particularly arbitration – there are significant opportunities for both practitioners and clients. Some of the tools have been referred to above. Others include e-discovery, contract automation and legal research tools. Wider technologies include the use of blockchain and smart contracts in arbitration.
Dispute resolution at the transactional stage
Even though most of these tools are useful after a dispute has occurred, big data and AI may also help parties at the transactional stage, for example, to come up with a dispute resolution provision that better serves the underlying purpose and is tailored to the parties’ exact needs.
Machine learning tools, for instance, may be able to process factors like:
- The place of performance along with any mandatory laws which may apply resultantly;
- Where the parties’ assets may be located;
- The language that’s most appropriate, and;
- Which procedural rights/power of the tribunal would be ideal in each case.
Failed performance stage
By generating and storing real-time big data in regards to operational activities, combined with the integration of AI-driven data analysis, parties can more effectively anticipate, identify and address issues around contract performance the moment they occur.
This will allow all parties involved to identify with even more accuracy the context revolving around – or any justification for – failed, incorrect or incomplete performance. With all other factors being equal, this should enable parties to narrow down the overall scope of disputes, whilst increasing the scope for amicable settlement.
AI, in analyzing big data, can perform a vital role when it comes to assisting with dispute resolution.
So, are there any hidden perils or drawbacks?
On the one hand, improving the resolution of disputes and furthering commercial aims may be publicly desirable outcomes to aim for in the name of the common good – on the other, there are some very important things to consider.
Biases, for example, may come into software design. A piece of software is only as objectively “good” as the people who create it, so, if our own opinions and actions are subject to biases – whether conscious or unconscious – are we not also building these into our data? This is where responsible AI and ethics come into play.
There may also be difficulty gaining access to the type and volume of data required, especially in arbitration where proceedings are largely confidential. To what limit can AI and big data replace human judgment? How and where should the balance be struck and how should these technologies be effectively used in the best interests of the client and, more broadly, effective access to justice? Will the general thinking and approach of current arbitrators, institutions and practitioners keep pace with the inevitable advances and disruptions big data, machine learning and AI will bring in the world of dispute resolution and arbitration?
All of these are valid, pressing questions but, for now at least, the answer to all of them is, simply, time. Innovation is about trial and error, and as big data continues to evolve the world of arbitration we will truly be able to see – and react to – the human impact of its progress.
Closing Thoughts: The future of tech in dispute resolution
Fact check: businesses today demand the delivery of super-quick and super-efficient legal services, all at lower expenses and with a higher degree of certainty. Litigation and dispute resolution teams need to do more with less, and big data will be at the center of it all as more and more businesses go fully digital.
Embracing the benefits of disruptive technologies such as big data analytics and AI will provide some dispute practitioners with a serious competitive advantage, ultimately allowing them to provide a service their clients that is more efficient and perhaps, more cost-effective than before.
It is, therefore, important that practitioners are not left behind and can fully leverage the technological benefits of AI, big data and other similar technologies.
Our Faculty Says...
“The collection, review and production of documents is one of the most time-consuming phases of arbitration, particularly where there is a vast number of potentially relevant sources of information to review. Document automation tools and advances in machine learning are enabling arbitrators to manage complex data more efficiently and cost effectively. There are dozens of programs available on the market that can serve as a platform to host, manage, organize, sort, and transfer documents and submissions gathered and/or exchanged in an arbitration. The International Bar Association provides a helpful overview of the types of technology resources available for arbitration practitioners.”
https://www.ibanet.org/technology-resources-for-arbitration-practitioners
– Hussain Hadi, Head of Publishing and Technology at LexisNexis Middle East
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