Advanced Legal Analytics
Full course description
Information about the law is stored in legal texts: legislation, administrative decrees, court decisions, and other legal writings. Lawyers use this information to apply and reason about the law, and to predict legal outcomes. Legal reasoning, analysing legal texts, and predicting legal outcomes can also be done, in part, by artificial intelligence (AI). More recently, researchers have developed legal information retrieval systems by effective use of sophisticated machine learning and natural language processing technologies on publicly available legal documents to assist legal practice. The availability of such legal information retrieval systems has created opportunities for improving the efficiency and consistency of existing legal systems. The main challenge for semantic analysis is that legal texts are predominantly unstructured data. In Advanced Legal Analytics, you will learn about the following major topics:
- Introduction to Artificial Intelligence and Law
- Legal Information Retrieval Systems
- Machine Learning with Legal Texts
- Natural Language Processing for Legal Texts
- Semantic Analysis of Legal Texts
Lectures and tutorials. Online courses in DataCamp Academic will be used for learning Python.
Intended Learning Outcomes:
Upon completion of the course, a student is able to:
- explain the methodology of legal information retrieval systems;
- explain and apply fundamental concepts of legal artificial intelligence;
- identify technical and legal challenges with legal artificial intelligence;
- apply and evaluate machine learning methods for computational analysis of law; and
- perform programming tasks to engage in legal text analysis, search and prediction
Ashley, Kevin D. (2017). Artificial Intelligence and Legal Analytics. Cambridge: Cambridge University Press.
Other recommended reading and literature will be provided during the course.