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To Promote Innovation Let Non-Lawyers Earn Income From Legal Services

The rule of law is a great boon to liberty, enabling us to plan our lives.  Making law more transparent and less expensive to use also increases liberty because then more people can take advantage of that stability at lower cost. It is a particular boon to the poor and middle-class who cannot afford high-priced lawyers to help them see through a fog of law.

Fortunately, the ever increasing power of computation is creating new mechanisms to improve access to  law. As I described in my presentation this week at the Organization of Economic Cooperation and Development, machine intelligence is transforming legal practice.  It is making discovery of facts easier through predictive coding, permitting search by semantic concepts rather than just legal terms, generating simple but personally tailored legal documents, like wills and trusts, and helping predict the outcome of legal cases. Discovery, search, document generation, and legal prediction constitute a large part of legal practice.

The single most important structural change to accelerate such innovation is to permit non-lawyers and corporations to earn income from the practice of law—something that is forbidden by ethical rules in all our states. Currently, law firms lack the expertise and capital to actually create innovations themselves. As a result almost all the innovations in legal services come from outside the profession. And yet obviously combining lawyers and experts and in machine intelligence with the kind of incentives and resources that corporations can provide would create synergies to drive innovation.

In medicine we recognize that corporations can furnish core medical services, even if they are owned and operated by non-doctors. Indeed, almost all the large medical service corporations meet that description. And the doctors they employ are still able to fulfill the ethical responsibilities of their profession. So it should be with law.

At the OECD conference, Caroline Wallace of the UK Legal Service Board described how England’s and Wales’ recent legislation permitting Alternative Business Structures (essentially non-lawyer companies) to deliver legal services has improved efficiency, quality and innovation. Sadly, she also noted that much of the legal profession remained hostile to these changes and opposed further deregulation of the profession.

But the hostility of lawyers to deregulation is yet another reason to permit non-legal businesses to offer legal services. These businesses will provide a counterweight to the bar, which uses its legal expertise to protect its own interests at the expense of the public. Permitting non-lawyers to earn income from legal services thus not only promotes legal innovations but reduces the barriers to such innovations that lawyers devise.

Reader Discussion

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on June 16, 2016 at 12:32:15 pm

1) And just what sort of legal services would / should they provide? It would seem that you are advocating a level of *service* somewhat braoder than, say, a LegalZoom scenario.

2) One *could* get the impression from your essay that legal service providers are not corporations. They are and from personal knowledge I can tell you that many of these legal service concerns are larger and have more resources available than a medical device manufacturer as an example.

3) Machine intelligence is a) only as good as the human intelligence deployed to create its algorithms, b) unlike human intelligence, machine intelligence is susceptible to hacking and other forms of manipulation.
(Of course, we humans can avoid this by keeping our tinfoil hats tightly secured - how secure is machine intelligence?)

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gabe
on June 16, 2016 at 20:32:18 pm

1) Any legal services, Legalzoom is only the first step in a long road.
2) They are corporations, but they cannot be owned in any part by non-lawyers. So no outside ownership by tech experts.
3) Machines think faster than humans, and depending on the algorithm can learn things. Primarily computers are best at looking at large amounts of data (too large for any human to even read it all) and then deduce pasterns. It can be very useful in medicine (http://www.bigdataleadersforum.com/Content/Machine-learning-in-Medical-Big-Data). And this is only with current generation AI, next generation AI may be based on quantum computers and be substantially faster and more accurate. https://ti.arc.nasa.gov/tech/dash/physics/quail/

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Devin Watkins

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