61 Pages Posted: 23 Aug 2012 Last revised: 8 Oct 2014
Date Written: October 7, 2014
This article offers an historical, theoretical and practical perspective on law as an information technology. Law fundamentally concerns information — providing information to the community about the content of legal norms and, at least in its common law form, eliciting information about the world from the disputes before a court. The article first surveys law’s history as an information technology and shows how law is changed by the information technology of its day. The article then applies information theory to understand how the computer — the key technology of our day — is changing legal search and thereby the efficient form of law. Information theory focuses on the signal to noise ratio of communication. The key to progress in creating a better computerized legal search engine is to reduce the signal to noise ratio in the link between the user and the search engine. As this ratio decreases, we show that legal search translates the uncompressed form of legal information into an algorithm for predicting what the law will be in a particular situation.
The ongoing improvement in legal search is transforming the optimal form of the law by changing the cost of finding it. It rebalances the weights in the classic debate between rules and standards. In particular, exponential increases in computational power make standards relatively more attractive than rules by decreasing the costs of their application. These same increases also allow us to embed information gathering processes within the law itself by creating what we call “dynamic rules.” Dynamic rules are rules that change automatically in response to changing empirical information. Such rules are already beginning to be enacted by legislatures. Since we believe that standards and dynamic rules are likely to be prevalent legal forms of the coming era, we close our article with a comparison of their relative costs and benefits.
Keywords: Information Technology, Rules and Standards, Information Theory, Codification
JEL Classification: K10, K19, K30, K39
Suggested Citation: Suggested Citation