LawtechUK has published the results of a consultation it carried out with legal professionals, organisations, and industry experts. It sought case studies about machine learning (ML) to understand ML’s current application in legal services and how legal service regulators could support responsible use to benefit consumers.
The case studies identified five broad types of ‘function’ ML powered systems were performing when being used in legal services, which included:
- Administrative: automated triage systems to support client and matter intake, collecting and organising documents;
- Profiling: profiling consumers to assess their understanding of legal text or identifying vulnerability to help tailor advice to different clients and achieve the best outcomes for different circumstances;
- Search: identifying relevant court judgments;
- Legal risk identification or prediction: in transaction or property due diligence, e-discovery or insurance fraud; and
- Legal text generation: contract drafting.
LawtechUK found that consumers of legal services stand to benefit from responsible use of ML. ML developers of legal services understand the risks involved and how to mitigate them. There is potential for ML to amplify existing disparities within the legal services market, but these disparities appeared to support a well-functioning, competition market that could drive better outcomes for consumers. Data forms the foundation of the ML opportunities for the legal sector. Many respondents emphasised that access to structured, high quality data will be essential to improving the accuracy of ML systems and mitigating the risk of bias. Consequently, the absence of sufficiently large data sets will likely stifle innovation in this space, even for the largest providers.
LawtechUK recommendations
Based on feedback, Lawtech has highlighted several outstanding challenges facing the industry. While LawtechUK may not be able to take all thee actions forward, it would like to encourage the regulators and other market participants to tackle them soon, especially in respect of:
- More research should be carried out to understand the potential benefits that the development of ML powered legal services systems can deliver to consumers and how best to achieve those benefits;
- There is an opportunity for legal service regulators and legal trade bodies to drive responsible use of ML for the benefit of the consumer, while providing support and guidance to regulated entities to do this;
- There is an apparent demand for more research and development funding as well as general support for innovators to develop, test and scale ML-powered uses cases ghat improve accessibility of legal services, whether through the Lawtech Sandbox or incubator style support.
- To facilitate closer collaboration with the insurance sector, the Regulatory Response Unit should host a meeting with PII insurers to raise awareness of the considerations and implications of AI and the emerging use cases in legal services to support a better understanding amongst insurers; and
- A robust data ecosystem will facilitate further innovation in this space, and as such it is critical that improved data practices are promoted and collaboratively channelled across the legal industry.
