Emergence of contract standards and its future impact on legal education.

AuthorMartin, Kingsley
PositionSymposium on Contracts

    Let me start with a story. It was almost thirty years ago that I graduated from Harvard Law School and joined my first law firm. I distinctly remember my first assignment, which was to draft a credit agreement. Despite my education, I had no clue how to perform the assignment. I had to do it the same way as everyone else, which was to go around the corridors, bang on some doors, get some examples, sit down and start to read them. I have no doubt that my first few attempts and, in all likelihood, years' worth of drafts, were sub-standard. This is what, in part, motivated me to focus my career on technology and law.

    Earlier this week, I gave a presentation to students at a leading law school and I am sorry to say that todays' law students are no more prepared to perform my first assignment. I asked them three simple questions: "By show of hands, how many of you in the room are interested in a career in law?" One hundred percent. "How many of you are interested in combining some aspect of technology with your legal career?" Zero. "How many of you are worried by the rise in technology as a potential threat to your chosen career?" One hundred percent. It just didn't add up in my mind. Using these questions as a springboard, I first sought to show how technology can better prepare our students. Second, I wanted to address their fears. It is apparent that many students are concerned that technology might take away their jobs. My goal was to explain that technology is an incredible opportunity.

    Over the past few decades, the legal profession has narrowed to serve just the one percent. Lawyers working in this space, of course, enjoy a very satisfying and financially rewarding life. The 99 percent is also a massive market opportunity. However, we may not be able to meet the needs of this market in the old fashion way, training lawyers by rote learning. We must harness technology to help us serve the broader market more efficiently.


    In order to take advantage of technology, we must better understand how the machine works. We know technology today is getting ever more powerful. Already, a computer can drive a car. A machine can fly an airplane. It can perform brain surgery. The question I raised is whether a computer can draft a contract? This is what I want to explore with you today. How far can it go? What can it do? How can it help? What are its limits?

    On the one hand, we have the rise of the machine, exemplified by IBM Watson. Watson first beat the world's best chess player. It has beaten the best contestants on the TV show, Jeopardy. Now, Watson is learning medicine and is already considered to be one of the best diagnosticians in oncology.

    On the other hand, we are trained to question. Lawyers are skeptics. One line of doubt holds the opinion that while a machine can perform incredible computations, it cannot think. A good example of this position is described by Professors Dreyfus and Dreyfus in title, Mind over Machine. (1) In the book, the authors assert that a machine can never replicate human though and therefore strong AI (artificial intelligence) will never work.

    However, we do not need to reproduce human intelligence in binary form. It matters less how we solve problems. We are more concerned with results. Indeed, if we compare results--who won--what is the difference between intelligence, judgment, and brute force?


    We are working our way through training technology to expand our intellectual capabilities. The evolution mirrors the way that we learn. There are three key stages to machine learning.

    Stage one is to find the relevant material. In learning a new area, we need source material, just as I gathered as part of my first legal assignment by asking more experienced lawyers. We need the relevant cases or prior contracts. Today, we are less likely to go to the library or form file. This stage is automated. We use a computer to find the sources. The key technology applied in this stage is search.

    Stage two--once we have gathered the relevant sources--is to review the material and identify the relevant elements: the relevant issues in the case, or the relevant elements of a particular transaction. This is how we learn over time: by reading many examples. And, this is the second stage of automation which applies the emerging technology of analytics.

    Stage three is to determine the optimal outcome. What is the best argument to make in a case? What is the best structure of a transaction? This capability, on the bleeding edge of automation, is the focus of "big data" and expert systems.

    Let's review some live examples. On the screen is a...

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