Harry Surden of the University of Colorado is scheduled to give a presentation entitled Machine Learning Within Law , October 9, 2014 at Stanford Law School.
The event is sponsored by CodeX: Stanford Center for Legal Informatics, and is part of the CodeX Speaker Series.
Here is a description of the event, from the announcement:
Professor Surden will discuss some current and future applications of machine-learning within law. Legal practice is thought to require advanced cognitive abilities, but such higher-order cognition remains outside the capability of current machine-learning technology. Is it possible then to automate certain legal tasks despite this technological limitation? In some contexts, the answer may be yes due to a core principle: tasks that are normally thought to require human intelligence can sometimes be automated through the use of non-intelligent computational techniques that employ heuristics, patterns, or proxies capable of producing useful, “intelligent” results. He will then explore automation in the context of legal tasks currently performed by attorneys, including predicting the outcomes of legal cases, finding hidden relationships in legal documents and data, electronic discovery, and the automated organization of documents.
Click here to view Harry Surden’s article “Machine Learning and Law” [...]
Filed under: Applications, Presentations, Technology developments, Technology tools Tagged: Artificial intelligence and law, Big data and law, Big data and legal information systems, CodeX: The Stanford Center for Legal Informatics, ediscovery, Electronic discovery, Harry Surden, Innovation in law practice technology, Innovation in legal technology, Law practice technology, Law practice technology innovation, Legal big data, Legal data analysis, Legal data processing, Legal evidence information systems, Legal information organization, Legal machine learning, Legal natural language processing, Legal prediction, Legal technology innovation, Legal text analysis, Legal text processing, Machine learning and ediscovery, Machine learning and law, Machine learning and law practice technology, Machine learning and legal data analysis, Machine learning and legal prediction, Machine learning and legal text analysis, Machine learning and legal text processing, Machine learning and quantitative legal prediction, Natural language processing and law, Organization of legal information, Quantitative legal prediction, Statistical methods in legal informatics, Statistical methods in legal text processing
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