Legal Innovation Careers: The Legal Analyst + Data Science Expert

March 6, 2018
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Originally published on High Performance Counsel. Written by Jason Moyse and Lisa Culbert.

Numbers, graphics, visuals and more. These are the inputs and outputs that matter for the 21st Century Legal Professional. Law is much more than the text narrative – despite a tradition of resistance to move beyond the written word.

No one said there would be math

Numbers and the law? This may seem a crazy thought for many who went to law school thinking math or science aren’t really their thing. Yet, tomorrow’s lawyers and an increasing number of present practitioners draw upon the field of data science as practices transitioned far beyond verbose language and treatise-like memos which are traditional tools of trade for the profession.

When we talk about "Data Science", what are we really talking about?

Data Science refers to methods, processes, and systems that extract knowledge or insights from data, either structured or unstructured, to drive meaning, intelligence and context for making decisions.

Information gathering <-> Analysis <-> Decision-making 

Among the results, enhanced productivity and reduction in cost of legal services.

For example, a data scientist or analyst could apply this skillset to answer questions like:

  • How much staff time (and whose time) does it take to negotiate a standard agreement?
  • What part(s) of this could be automated and where can lawyers and others involved add the most value?

Tools like Clocktimizer (using Natural Language Processing of lawyers’ docket narratives to provide compelling analytics for insights on pricing and profitability) can certainly help, as can project management and data science oriented legal teams

Data science and due diligence?

This is where innovative thinkers like Laura van Wyngaarden and Konrad Pola and their startup Diligen come in. Diligen’s software is built on machine learning to help lawyers review contracts faster, find relevant provisions and produce contract summaries – instantly.

Laura and Konrad met at Oxford and a few years later, Konrad having spent many long nights and weekends in his corporate law practice engaged in laborious, mostly manual, due diligence reviews found himself asking: why not apply AI to due diligence?

Diligen was born and through the leadership of Konrad (CEO) and Laura (COO), the tool is driving efficiencies and effectively extending data science into law firms and in-house legal teams.

Laura explains that essentially the tool works by:


1 – scanning a significant volume of documents;


2 – outputting (in a few minutes or less) a summary of key information for each contract that the tool has already been programmed to extract (via machine learning) including parties, key dates, governing law and other material clauses.


3 – enabling the user to review the output and quickly zoom in on what matters.


In an M&A transaction, a top gating question of whether the target (to-be-acquired) company has any change of control restrictions set out in its existing volume of contracts can quickly be assessed. Diligen can read hundreds of contracts and a few minutes or less, deliver an output of the handful that have potential restrictions that could block the deal. The reviewing lawyers can then dive deeper into those contracts to consider the specifics of the restrictions.

Compare this with the traditional manual review of the same batch of contracts which entail weeks+ of review and expense. Diligen can save massive amounts of time and money.

Do you need to be a data scientist to use it? No but… Laura explains the intelligence within the tool is the result of:

(A) lawyers and experts who train, teach and regularly try to “trick” the machine to enhance its ability to pick up all instances of a provision;

and

(B) the “feedback loop” involving the user’s review of the output for what was extracted and excluded, correctly or not. Through this feedback loop, the tool is steadily tailored to the work of its users and the user becomes a data scientist by engaging with and training the tool.

So, robot (tool) and lawyer (human) can play together! This is augmented AI in practice and as Laura thoughtfully explains,  addresses one of the most common misconceptions of AI that robots (technology) can replace lawyers. Far from it. Diligen is a tool. It expands capacity to do things faster while still requiring lawyers to train, teach and review; creating the opportunity for lawyers to focus on more meaningful work (instead of voluminous, routine and mundane tasks).

That’s music to our ears. For those looking to build out their 21st Century data science skills, Laura helped break down key attributes:

  • An interest in technology;
  • An interest in coding (not necessarily learning how to code but understanding the “language of code” as an asset); and
  • Willingness to experiment and engage with technology –as an ally rather than a threat.

By playing and embracing new tools like Diligen, the 21st Century legal professional can gain an appreciation of data science and enhance their ability to navigate and deploy solutions in “big data” environments while leveraging AI for better client service.

Stay tuned for our next “alt” legal career profile – Business Advisor & Industry Expert.