The Regulating Automated Legal Advice Technologies (RALAT) project is an initiative of the Melbourne Networked Society Institute, involving a team of researchers from law and computer science. Our first Discussion Paper, which aims primarily to map the field is available here.
The paper classifies automated legal advice tools/technologies (ALATs) by reference both to function and intelligent capability. Functionally, it identifies five subsets of technology:
• Specialised standalone technologies, such as legal chatbots, apps and virtual assistants,
• Enablers of legal advice such as legal automated drafting, legal document review and legal algorithms,
• Further enablers of legal advice such as legal data analytics and predictors, and legal artificial intelligence,
• Automation of legal advice with truly smart contracts, and
• Sets of ALAT technologies enabling NewLaw business models and legal technology companies.
In terms of capability, a range of technologies are found to exist from simple non-AI tools relying solely on hard-coded decisions through to “smarter” or “more intelligent” sophisticated technologies that use deep learning and can parse text, learn causations and correlations from data, and reason about these to make predictions.
We find that the market in ALATs is developing rapidly. Most applications have entered the market since 2014, with the greatest activity in the US – likely reflecting the greater availability of venture capital. ALATs are both new and at varying levels of sophistication, with the majority at the lower end of the ‘intelligence’ scale.
ALATs are identified as a critical technology in terms of market disruption. The giving of legal advice is a central function of the legal profession. ALATs create opportunities, notably of commoditisation of advice-giving. The potential for automated legal advice to reduce costs and open-up latent markets is significant, particularly in the context of current debates around declining access to justice. ALATs also highlight challenges to market incumbents across the industry, for example, as technical legal expertise becomes increasingly open to automation. US corporates like LegalZoom and Rocket Lawyer are examples of ways non-lawyer entities may seek to enter and disrupt traditional markets for smaller business and consumer legal services. Policy questions arise as to the risks such disruptors may pose to consumers, and how regulation should respond (if at all).
The challenge to legal services regulation posed by ALATs is explored in sections 3 and 5 of the paper. Section 3 introduces the problem in terms of the wide definition of legal practice in Australia, which reserves legal work to the legal profession. This section also explains how regulation demarcates the provision of (unregulated) legal information from (regulated) legal advice-giving. This regulated boundary between information and advice could prove to be a critical zone of engagement, determining the impact of new market entrants, including unregulated disruptors. While controls on advice-giving have consumer safety justifications, the development of automated intelligence potentially changes the risk environment. To this extent, automation re-opens important questions regarding the scope and proper function of legal services regulation.