Orin Kerr on Engineering vs Law

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Orin Kerr is a legal scholar specializing in cybercrime law.  He is a Professor of Law at the George Washington University Law School.  Before transitioning into the Law, he majored in Mechanical Engineering at Princeton and Stanford.

Professor Kerr has drawn my attention to an item he posted in June 2007 on his thoughts about making the transition from Engineering to Law.

Professor Kerr explains:

Studying Engineering and Studying Law: I enrolled in law school after engineering graduate school, and people occasionally ask me if I have advice for engineering graduates planning to study law. I get questions like, “Is studying engineering good preparation for law school?” Or, “How should I make the transition from engineering to law?” I thought it might be worth blogging about this, as my answers hinge in part on something that should be of broad interest to readers: the differences between how engineers and lawyers look at the world.

Here is my response to selected passages from Professor Kerr’s essay.

Studying engineering trains students to think logically, step by step, and that kind of logical thinking can sometimes help students see relationships more easily than students with some other backgrounds.

True enough, but more importantly, engineers employ functional models of the system they are engineering. Reasoning about the behavioral dynamics of a complex system by crafting and solving functional models is arguably the most powerful tool for thought that the engineer brings to an enterprise.

Engineers study nature, while lawyers study something man-made.

Huh? When I was doing Network Planning at Bell Labs, I was studying the operational characteristics of the (man-made) telephone network and the (natural) behavior of the humans who were using the network. I had models for the operational characteristics of the physical network and I had models for the behavior of the humans who were using it. By combining these models, I was able to optimize the operating characteristics of the network to match it to customer needs and preferences while minimizing operational costs.

Mostly I was doing model-based reasoning, building and solving system models to devise best practices.

Whereas in engineering, the “laws” come from nature, in the law we have man-made rules devised under man-made rules for making those rules.

In doing systems engineering for the telephone network, it didn’t really matter which features were governed by the laws of nature, which features were governed by principles of operation hard-wired into the design of the network, and which features were governed by the practices and behaviors of human beings.

Among the practices that we cared about were the Bell System Practices, which were the written rules and guidelines for the operating staff of the Telephone Operating Companies. Part of my job was to review and revise Bell System Practices which were essential to ensure near-optimal operational management of the network.

Sometimes we found antiquated rules that said things like, “If Condition X occurs, apply Practice Y to handle it.” Most of the time, such rules proved to be inadequate at best and problematic at worst.

In virtually every case where we found dysfunctional rules of that sort, we replaced them with continuous functions that regulated the operation of the network much the way your automobile’s Cruise Control works. We built regulatory mechanisms that, to a good approximation, solved the system models of the systems we were managing.

This is how we applied the tools for thought from the STEM disciplines to create high-functioning systems that operated as efficiently and as gracefully as practical.

The first thing that I, as a Systems Engineer, would do when contemplating the man-made Rule of Law would be to craft a system model of its dynamics. Actually this is not very hard to do. The most important finding is that rule-based systems (like the Rule of Law) are inherently chaotic (in the mathematical sense). This defect can be easily remedied by replacing rules with well-crafted functions, much the way we did so in the technocracy of the Bell System.

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