Can AI Tell Us How Many Laws We Really Have?

February 18, 2017

 

        Recently, in the course of my research on the impending effect of artificial intelligence on the application of the law, I needed to look up when scholars estimated the Code of Hammurabi to be written, which I was taught in school to be the oldest surviving legal code in the world. Well, it turns out not to be true, and it has not been true since the 1950’s. In fact, the Code of Ur-Nammu currently holds the title of the oldest surviving legal code in the world outdating Hammurabi’s code by 300 years. The Code of Ur-Nammu resides in two partially destroyed clay tablets written in Cuneiform, and the tablets contain about 30 legible laws. The Code describes for each law both the crime and the punishment. The punishments include death for crimes like murder and robbery and fines for other crimes.

 

         A marvelous book called The Codex Collections from Mesopotamia and Asia Minor contains a complete translation of the surviving Ur-Nammu laws. The laws are practical and clear, and they offer a view into the issues of people living in Ur over 4,000 years ago. For example, “If a man presents himself as a witness, but is demonstrated to be a perjurer, he shall weigh and deliver 15 shekels of silver.” Clear and precise. Reading through these laws and marveling at their age and clarity, I began to think about the evolution of law and the growing complexity of our legal system. I wondered how many laws we have currently in the legal code of the United States.

 

        Legal librarians often receive the question of how many laws we have, and it turns out that nobody knows! In searching for some estimation, I came across an article in the Wall Street Journal from 2011. The authors found that legal scholars have struggled for years to determine the number of federal crimes on the books. In the early 1980s, Ronald Gainer, then an official at the Department of Justice, attempted but ultimately failed to tally up the number of crimes dispersed across the 23,000 pages of federal laws. After two years of counting, Mr. Gainer and his team could not furnish a definitive number and left the final estimate at around 3000 laws. Since every law ever written by the Federal Government is contained in the United States Code, counting the laws would seem to be a tedious but simple addition problem; however, some laws replace old laws or amend a part of an existing law. To count the laws requires knowledge of the complex interrelatedness of our legal system. Now remember that Mr. Gainer’s attempt to count all the laws only focused on federal criminal laws and does not include civil code or the vast landscape of Executive Branch “rule making” written to support laws passed by Congress. In total, the laws of the United States may be in the tens of thousands.

 

        The vast and complex world of law today stands in contrast to the clear, tiny Code of Ur-Nammu. One could imagine that people could easily memorize the code back in Ur. Mr. Gainer’s work highlights the complex challenge of knowing how many laws we have and the, interpretation of those laws and regulations. Unless Congress were to simplify the legal code much like the often-promised simplification of the tax code, law will move into higher orders of complexity. No one person can know the vast entirety of the legal space today. However, vast data and high complexity lends itself beautifully to the emerging artificial intelligence systems that consume millions of books, laws and documents in a matter of days. Smart systems that can learn the laws and their interrelatedness may be the powerful new assistants to attorneys and law makers. Armed with intelligent machines the law may be easier to navigate, and eventually we may even know how many laws we have.

 

 

Dr. Smith’s career in scientific and information research spans the areas of bioinformatics, artificial intelligence, toxicology, and chemistry. He has published a number of peer-reviewed scientific papers. He has worked over the past seventeen years developing advanced analytics, machine learning, and knowledge management tools to enable research and support high level decision making. Tim completed his Ph.D. in Toxicology at Cornell University and a Bachelor of Science in chemistry from the University of Washington. 

 

You can buy his book on Amazon in paperback here and in kindle format here.

 

 

 

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