Professor Dr. Kevin Ashley of the University of Pittsburgh gave a presentation entitled Toward Integrating Computational Models and Legal Texts, on 6 February 2014 at Stanford Law School.
Here is a summary:
This talk will survey some techniques and prospects for enabling computational models of legal reasoning to work directly and automatically with legal texts to perform legal problem-solving tasks. For example, users of commercial legal information retrieval (IR) systems often want to retrieve not merely sentences with highlighted terms, but arguments and argument-related information, that is, argument retrieval (AR). The talk will illustrate how argument-relevant information could be extracted and applied to retrieve arguments from legal decisions. A second example involves techniques for annotating state statutory texts in a particular domain (dealing with public health emergencies), both manually and using machine learning, so that policy analysts can compare states’ regulatory schemes using network analysis. Related AI and Law work on information extraction from cases and statutes will be highlighted.