Artificial Intelligence and Law — Barcelona 2009

AI & Law

Live from Barcelona, we are on the road at the International Association for Artificial Intelligence and Law.  Henry Prakken has just delivered the keynote address and we will soon be giving our presentation. The conference is interesting as it embraces a wide range of topics and intellectual traditions. For example, there is a significant emphasis on ontological reasoning, computational models of argumentation and the use of XML schemas. In addition, there are a number of folks using graph theoretic techniques and applying them to the development of the law. It has been a nice few days and we have enjoyed our time here. Tomorrow, the trip continues…. 

Tax Day! A First-Order History of the Supreme Court and Tax

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Click to view the full image.

In honor of Tax Day, we’ve produced a simple time series representation of the Supreme Court and tax.  The above plot shows the how often the word “tax” occurs in the cases of  the Supreme Court, for each year – that is, what proportion of all words in every case in a given year are the word “tax.”  The data underneath includes non-procedural cases from 1790 to 2004.  The arrows highlight important legislation and cases for income tax as well.

Make sure to click through the image to view the full size.

Happy Tax Day!

When is the first term enough?: On approximation in social science

Research in the academic world suffers from the “hammer problem” – that is, the methods we use are often those that we have in our toolbox, not necessarily those that we should be using.  This is especially true in computational social science, where we often attempt to directly import well-developed methods from the hard sciences.

To prove the point, I’d like to highlight one example we’ve come across in our research.  In Leicht et al’s  Large-scale structure of time evolving citation networks, the authors apply two methods to a simplified representation of the United States Supreme Court citation network.  Both of these methods rely on complicated statistical algorithms and require iterative non-linear system solvers.  However, the results are consistent, and they detect “events” around 1900, 1940, and 1970.

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One  first-order alternative to detecting significant “events” in the Court would be to count citations.  One might suspect, for instance, that the formation or destruction of law might go hand-in-hand with an acceleration or deceleration in the rate of citation.  Such a method is purely conjectural, but costs much less to implement than the methods discussed above.

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This figure shows the number of outgoing citations per year in blue, as well as the ten-year moving average in purple.  The plot shows jumps that coincide very well with the plot from Leicht, et. al.  Thus, although only a first-order approximation to the underlying dynamics, this method would lead historians down a similar path with much less effort.

This example, though simple, is one that really hits home for me.  After a week of struggling to align interpretations and methods, this plot convinced me more than any eigenvector or Lagrangian system.  Perhaps more importantly, unlike the above methods, you can explain this plot to a lay audience in a fifteen minute talk.