A Brief History of Data Science in Legal Tech


Picture a Lawyer! One of the first images that will spring to mind for many is that of people in suits, labouring over tremendous piles of printed case law. Although suits are still the norm, the rest of this picture has become somewhat redundant. For the most part, the legal industry is characterized as being quite conservative and lethargic regarding innovation. Still even, the digital revolution has severely altered the landscape, tremendous piles of paper have been replaced by computer screens and data bases.

Software and digital services which either support law professionals in their day-to-day workings or automate processes entirely are described as Legal Tech. Academic literature on this field is quite sparse since for the longest time the technological solutions law professionals utilized were quite conservative, holding with the aforementioned slow-to-adapt stereotype. This is sure to change as innovation in legal tech is quickly gaining momentum – but more on this later – lets first look at where it all started.

The first wave – sometimes dubbed LegalTech 1.0 – swept over the legal realm since the early 1980s, slow at first but becoming ever more prevalent as technology progressed. The most prominent facet of this wave was digitalization, with Legal Databases such as Westlaw popping up. These databases, at first available through massive terminals installed in law offices, replaced the tremendous piles of printed case law, with online portals such as EUR-Lex making EU law, case-law and much more available online at the press of a button in current times. Although revolutionary to how lawyers could access the data necessary for their job, this did not yet introduce data science to the legal profession.

Mark Cohen of Forbes went as far as describing the legal sector as a “data wasteland in the digital era”. Next to its generally conservative characterization, there is one straightforward reason for this; to date, the incentive for innovation was lacking. Law is very labour intensive, but the (often enormous) labour costs that are raked up can be passed on to the client – there is no need to reduce them through technology. But this is beginning to change – LegalTech 2.0 is gaining momentum – with data science at the forefront of revolutionizing Law and the legal landscape.

LegalTech 2.0 ventured further than solely aiding the day to day workings at law practices – instead automating varying processes at law firms. This happens across the board; both for internal operations such as intelligent legal billing (e.g. Apperio) or knowledge-management (e.g. Intelllex); as well as for client-facing processes. One striking example of this is Flightright – which enables consumers to claim compensation for cancelled flights entirely online.

But what is it that has been able to break through the technological lethargy of Law? There are two factors at play here. For one, law firms are beginning to realize that data is essential to streamlining internal operations – enabling them to reduce costs that they are unable to pass onto their clients, assess and mitigate risks and measure, interpret and utilize performance figures. But perhaps, more importantly, external pressures are forcing them to accept and strive for innovation. Clients pressure is maybe the most dramatic factor. But many others, ranging from a changing demographics to competitive pressures introduced by legislation - such as the Legal services act of 2007 in the UK (enabling alternative business structures (ABS) in the law industry), also contribute.

With LegalTech our gaze should be set ahead with great anticipation, both for a broadening of 2.0 solutions and for LegalTech 3.0 which promises to fully automate legal processes. Disrupting the legal landscape dramatically! Putting aside the internal processes which invite Data Science solution, instead focusing on Client-facing services, Data Science can find a wide range of implementation.

Machine learning alone can enable much more than its apparent utilization regarding the evaluation of law databases and discovery – which used to be incredibly labour intensive. Case assessment and prediction, which used to be a skill only acquired over time based on experience, can be made available across the board. By feeding case data into machine learning algorithms, that can then help predict the outcomes of potential or current cases. predictive analysis can be a valuable tool. Data Science can be used to get insight on the opposition more effectively, to fine-tune cases for specific judges based on their past rulings and much more.

Venturing further into LegalTech 3.0 it can, when observed from the status-quo, even acquire a somewhat unworldly character. If applications begin automating entire legal processes, trained law professionals will start losing their monopoly on practising Law. Blockchain systems can replace notaries in real estate. Online dispute resolution can replace judges in commonplace cases. AI based Chatbots can replace lawyers giving legal advice. Evidently, over the next years, as technology progresses, law and data science will become ever more involved, and thereafter the legal landscape will change dramatically.

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