How Big Data Is Disrupting Law Firms And The Legal Profession

Author

Bernard Marr, Contributor

January 26, 2016

The legal system generates a huge and ever-increasing amount of data. Each new case brought to court (and there are 350,000 in the US alone each year) increases the body of knowledge that a lawyer has to get to grips with to do their job. Judicial ruling, precedents and interpretations of legislature all create more data and amongst it all – within witness statement, court logs and judge’s summaries – will be hidden facts and insights that could help win legal arguments.

So it is surprising that until recently there has been little innovation in the way that the legal profession uses Big Data. But some believe that is all about to change with the arrival of a new breed of data savvy lawyers and legal professionals.

The first Big Data tools to be made available to lawyers generally focused on billing, time management, marketing and customer relations functions – in line with their incursions into many other industries. Now, lawyers and those developing tools for the profession are starting to think about how this technology could be applied to the fundamental research and case preparation which is the core of their job.

Currently, the world of legal data-driven research is ruled by two entities – LexisNexis and Westlaw. These giants hold databases containing huge amounts of case details and are often the default starting point for legal researchers. However they mainly function as search engines and offer little in the way of advanced analytical tools.

One challenger which is attempting to apply more sophisticated technology to this vast and arcane body of knowledge is Ravel Law. Established in 2012 by two lawyers with backgrounds in analytics, they provide services designed to help legal professionals draw insights and connections using advanced analytical algorithms.

One of their services– Judges Analytics – lets lawyers search through every decision made by particular judges to find those most likely to be sympathetic to their arguments. The data is visualized through Ravel’s dashboard in a way that makes it easier to spot connections and opportunities that otherwise would have been missed.

Co-founder and CEO Daniel Lewis told me “When Nik [Reed, the other co-founder] and I met at Stanford, we had both come from previous work where we’d been exposed to how Big Data was playing a big role in changing other industries. Nik had come from politics and worked on election campaigns with Obama, and I had worked in policy, as well as played baseball through college, and I’d seen how Big Data had really changed the world of sport.

“We realized that the legal field had not really been touched by Big Data at all – so we designed Ravel to reimagine the search process and give lawyers data driven tools to sift through millions of documents to see what’s important, and understand how they can use it effectively.”

Ravel Law has also undertaken an ambitious Big Data project in cooperation with Harvard Law School, which aims to digitize the faculty’s entire US case law library – the country’s largest outside the Library of Congress – and make it available to anyone, online, for free by 2017.

Every page of every document will be scanned as well as converted to computer text with optical character recognition technology – meaning it will also be available for analysis through Ravel’s platforms, which are built around natural language processing and machine learning capabilities.

The legal profession is traditionally one of the most conservative fields of professional or academic activity, however “It’s become a lot more receptive and interested in technology over the past several years”, Lewis tells me.

“In part it’s being driven by a new generation of attorney who has entered the law in the past 5 or 10 years and have high expectations about what technology should do for them.”

His co-founder Nik Reed adds “One of the most exciting moments for me starting at law school and having come from working on Wall Street was realizing I wasn’t alone – the days when lawyers were all English Literature or philosophy majors are behind us now, my classmates included a lot of people from finance and one who had a PhD in bio chemistry from MIT. These are people who are familiar with quantitative analysis and datasets, and they are yearning for richer information sources and better analytics technologies. It probably wouldn’t have gone down very well 30 years ago with the kind of people who were lawyers back then.”

Digitization and Big Data can undoubtedly bring big benefits to the legal profession. Some are obvious, such as freeing up space formerly needed to keep mountains of case files in filing cabinets, to the less obvious such as finding unexpected judgments or decisions which could swing a case in favor of a data- savvy lawyer.

It should also lead to a greater degree of efficiency and transparency, which will eventually benefit all of us. Reducing the time it takes lawyers to complete research and casework will lead, in theory, to reduced bills, and improved access to the justice system for everybody. As well as this, judgments which are handed down will be more likely to be correct and safe, when they are informed by accurate, up-to-the-minute data, which will reduce the need for time consuming and expensive appeals and retrials.

All this of course leads to the possibility that one day judges and lawyers will be replaced by computers – which will be able to resolve problems to the letter of the law without being distracted by human concepts such as bias, emotion or failures of logic. This seems far-fetched, and of course it is at the moment. But it isn’t that difficult to foresee a time when routine but time consuming procedures such as parking ticket appeals or contract disputes could be settled by algorithms. However I expect it will be some time before we see a computer bring down the gavel to send someone to jail.

This article was written by Bernard Marr from Forbes and was legally licensed through the NewsCred publisher network.


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