Artificial Intelligence is the science of making computer software that reasons about the world around it. Humanoid robots, Google Goggles, self-driving cars, even software that suggests music you might like to hear are all examples of AI. In this class, you will learn how to create this software from two of the leaders in the field. Class begins October 10.” Check out the syllabus here. Although I have previously highlighted Academic Earth – I am a little late on this New York Times coverage available here. See also Andrew Ng’s class on Machine Learning (which is also available right now on Academic Earth).

Kevin Slavin argues that we’re living in a world designed for — and increasingly controlled by — algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine: espionage tactics, stock prices, movie scripts, and architecture.

Very interesting talk and note this could just as easily say – Law’s Future? There’s an App for That. Generated by the nexus of available technology and the current legal employment crisis there appears to be a growing app / “garage guys” culture breaking out. LawTechCamp, New and Emerging Legal Infrastructures and other related conferences showcase just some of the app style innovations that are being generated in the legal marketplace. I guess you can say there is nothing more dangerous than a bunch of smart folks who get pushed into a corner — forced to innovate for a want of high quality alternative options. Change is on the march and my bet is there is more disruption in the windshield than in the rearview. As my old football coach liked to say — better keep your head on a swivel!

Our paper An Empirical Survey of the Population of United States Tax Court Written Decisions was recently published in the Virginia Tax Review. We have just placed supplementary materials online (click here or above to access).

Simply put, our paper is a “dataset paper.” While common in the social and physical sciences, there are far fewer (actually borderline zero) “dataset papers” in legal studies.

In our estimation, the goals of a “dataset paper” are three fold:

• (1) Introduce the data collection process with specific emphasis upon why the collection method was able to identify the targeted population
• (2) Highlight some questions that might be considered using this and other datasets
• (3) Make the data set available to various applied scholars who might like to use it

As subfields such as empirical legal studies mature (and in turn legal studies starts to look more like other scientific disciplines) it would be reasonable to expect to see additional papers of this variety. With the publication of the online supplement, we believe our paper has achieved each of these goals.  Whether our efforts prove useful for others — well — only time will tell!