Liability decision trees
How does an organisation filled with knowledge and experience, capture and make use of that in an increasingly disconnected workplace?
As a trainee solicitor in the early 1990s, much of my learning came by osmosis; sitting in with partners and other solicitors and hearing and seeing them work. Draft letters came back covered in red pen until they were deemed suitable to be sent out in the name of the firm. Letters that were deemed suitable one week were rejected the following week with a flick of the wrist and a sneer! In hindsight it probably wasn’t the most efficient way of learning but the fact of being around other people did help me to learn — and to identify who to ask stupid questions of. Fast forward 30 years and our new trainee has started in the middle of a pandemic. Five months in, she has only met most of the team over Zoom and her capacity for absorbing knowledge is inevitably going to be affected by the lack of an office environment. But this is a future that was probably inevitable and has just been speeded up by the pandemic.
So how does an organisation filled with knowledge and experience capture and make use of that in an increasingly disconnected workplace? How do we continue to service our clients efficiently whilst ensuring that the quality of the advice remains accurate and relevant? Can we use technology to capture the knowledge of experienced fee earners for the benefit of those still learning their trade?
Using artificial intelligence (AI) to map out how people think was once the preserve of science fiction. However, this is now at the core of work being done by Weightmans on legal decision support tools. For our lawyers and our clients, such software tools will bring many benefits including improved consistency, reliability, and speed of decision-making. For our junior lawyers in particular it will provide them with guidance without being prescriptive.
Partnering with the University of Liverpool we are making use of recent AI developments, particularly from the field of computational argumentation, to model legal reasoning. We are taking developments that had previously been restricted to use in academic scenarios and are putting them into practice in modelling the decision making processes lawyers use.
In the process some of us have had to learn a whole new language and a new collection of acronyms. Can I interest you in ‘ADFs’ (abstract dialectical frameworks)? No? Well, these are a useful means of capturing a legal process and decision-making but are only really of any practical use if what is captured can then be translated into an appropriate and user-friendly piece of software. We cannot expect a lawyer to work through an ADF manually and still hope to improve the speed of decision-making! However, with the use of a no-code automation platform, we have been able to translate the ADFs into user-friendly tools that will achieve just that.
The benefit of this methodology is that is it not static and we can move or add elements to it without affecting the underlying logic. This means that any future legal changes will not render the ADF or its software implementation obsolete. After initial success with creating ADFs for noise induced hearing loss (NIHL) and manual handling claims, the focus has now turned to “slip and trip” claims. The aim is to help our lawyers quickly assess the facts and merits of a case in order to make a reasoned decision on how to proceed.
In a legal system based on equity, considering any case is not just about the application of black letter law. A robot can tell you what a piece of legislation says but our common law system often changes to reflect society. How a case is likely to be resolved is always more nuanced. That is where experience combines with knowledge. The decision support tools and the ADF methodology fit with our ‘augmented intelligence’ approach. This sees us use technology to assist with the legal process, supporting our lawyers with particular tasks, rather than adopting a ‘computer says no’ approach.
AI assisted legal systems are undoubtedly in our future but transparency of decision-making, particularly if technology is used, is vital. Every first year law student is told that justice must not only be done, but also be seen to be done. Having tools where the decision-making is transparent and is assisting an individual in the decision-making process is an important check on what could otherwise become automated systems.
In an increasingly technological world, trust remains vitally important; both in the technology and our ability to use it. Maintaining trust by promoting accountability, clarity and transparent decision-making provide a starting point for trustworthy behaviour.
As a result of our collaboration, we have already won the award for ‘best use of technology’ at the Modern Law Awards 2019.