AI in the Legal Workplace: Collaboration or Competition?

Source: Dilbert


As AI systems become more widespread and versatile, they will undoubtedly have a major impact on our workforce and economy.  On a macro scale–that is, across the labor market as a whole–whether AI’s impact will be positive or negative is very much an open debate.  The same is true of the impact of AI on many specific occupations.  Roughly half of jobs in the United States are “vulnerable” to automation, according to a 2013 study.  But whether AI systems will prove “good” or “bad” for workers in a specific profession will depend in large part on whether AI serves as complement to human workers or acts as a replacement for them.

In the legal profession, for instance, the rise of predictive coding and improved scan-and-search software has given law firms the option of automating some of the most time-consuming (and therefore expensive) aspects of identifying relevant documents during litigation, a.k.a. document review.  Document review has long been bread-and-butter work for young lawyers, especially at law firms that handle complex litigation cases, which can require sifting through and poring over thousands or even millions of pages of documents.

In an “AI-as-collaborator” scenario, predictive coding identifies potentially relevant documents and then a human lawyer reviews the identified documents to confirm their relevance and determine whether they are subject to privilege.  AI thus helps lawyers be more efficient at conducting document review and frees them up to focus on higher-level legal work.  In a best-case scenario (well, for lawyers at least), law firms’ clients might feel more comfortable with pursuing litigation and less willing to settle cases early if they knew that they wouldn’t have to spend ungodly amounts of money on armies of lawyers reading through mostly useless emails.  In this scenario, AI helps improve productivity and increases the overall value of lawyers’ work without reducing demand for lawyers.

On the other hand, market forces might force lawyers to pass on the cost savings achieved by automating document review to their clients, in the form of having fewer lawyers (or fewer hours per lawyer) on each case.  Clients could then take the savings and spend it on something more useful other than legal fees.  If that’s the main impact of predictive coding, then AI will lead to a reduction of the number of jobs available for lawyers and/or a reduction in wages for lawyers.

Of course, document review is rather low-hanging fruit when it comes to the automation of lawyers’ work.  Taking the information contained within those documents and using it come up with a good legal argument is quite another matter–although given that it’s been over half a decade since Watson beat the pants off Ken Jennings and proved that AI can decode the wordplay of Jeopardy! clues and come up with accurate responses, even seasoned litigators might not want to get too complacent.

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