The Wisdom of Using AI for Middle Value Arbitration Disputes

Client service in the legal profession is changing. Indeed, in the post-COVID-19 world, extraordinary change and the ability to adapt to that change has ruled the day. But, even before we were called upon to live virtual lives and make the most of technology to service and meet the novel needs of clients, there was increasing pressure in the marketplace to deliver better, more efficient legal services. In the area of dispute resolution, the costs of resolving disputes have continued to increase largely driven by the exponential increase in the amount of data involved. Add to that the complexities of dealing with that data over borders, and corollary discovery expenses, and costs skyrocket. Indeed, for some smaller value cases, counsel might even pass altogether on bringing forward a valid claim. In a recent University of Queen Mary survey focused on construction arbitration, 43% of in-house counsel believed that disputes needed to be valued between $11 million to $25 million to make the claims worth pursuing. With decreased liquidity in global markets and shrinking corporate budgets, businesses face even more complicated analyses to determine which disputes are "essential" or "non-essential" to take forward.

In the meantime, machine-learning technologies have found their way into virtually every business sector. Artificial Intelligence (AI) is transforming industries from health care to transportation. Although the legal profession has been somewhat resistant, AI applications have marched their way into the practice of law, and some have argued that current global conditions will only accelerate their widespread use. So what is AI exactly? Simply put, AI is highly advanced software that utilizes statistics, pattern matching and coding to perform tasks. It appears to think like a human, but is "smarter," in that it can use and maintain volumes of data that no human could. Current uses of AI technologies in the law range from "chat-bots" acting as a first point of contact to use of predictive coding for document review to elementary decision-support systems for simple commercial disputes. While these uses are growing, the question is whether AI can do more.

Up until now, the arbitration community has responded to some of the cost-benefit problem raised above by developing expedited provisions that seek to streamline proceedings. These improvements have been largely focused on lower-value, lower-complexity disputes. But, what about the middle value dispute? One can argue about what would constitute a middle value dispute but at its core, it might be a dispute that is moderately complex, or where the potential costs of bringing the action are significant considering the amount and interests at issue. In the current environment where global conditions challenge multiple business relationships at once (i.e., across jurisdictions or a global supply chain), companies are likely to face a number of these disputes and will require thoughtful dispute resolution techniques to resolve them in a cost-effective manner. It is here that AI may offer the most promise.