Friday, April 7, 2017 - 10:30am

Location:

2315 Doherty Hall

Speaker:

Matthias Grabmair Carnegie Mellon University, Language Technologies Institute

Event Website:

https://www.lti.cs.cmu.edu/lti-colloquium-11700

Matthias Grabmair

Search, Read, Argue and Predict:  An Introduction to Artificial Intelligence and Law

ABSTRACT  The field of Artificial Intelligence and Law studies how legal reasoning can be formalized in order, eventually, to be able to develop systems that assist lawyers in the tasks of researching, drafting and evaluating arguments in a professional setting.  To further this goal, researchers have been developing systems, which, to a limited extent, autonomously engage in legal reasoning, and argumentation on closed domains.  However, populating such systems with formalized domain knowledge is the main bottleneck preventing them from making real contributions to legal practice.  Given the recent advances in natural language processing, the field has begun to apply more sophisticated methods to legal document analysis and to tackle more complex tasks.  Meanwhile, the LegalTech sector is thriving and companies/startups have also been trying to tap into the legal industry‚Äôs need to make large-scale document analysis tasks more efficient, and to use predictive analytics for better decision making.  This talk will present an overview of the history and state of the art in academic AI & Law, as well as selected examples of current developments in the private sector.  Aspects in focus are case-based reasoning, legal text analytics, and the collaborative LUIMA project conducted by CMU, the University of Pittsburgh, and Hofstra University.

BIO  Matthias Grabmair is a postdoctoral associate at in the Language Technologies Institute at Carnegie Mellon University working with Prof. Eric Nyberg on solving problems in intelligent legal information management and intelligent natural language dialogue systems while also teaching at the institute.  His work is best described as (Legal) Knowledge Engineering or (Legal) Data Science.  It draws from artificial intelligence & law, knowledge representation & reasoning, natural language processing, applied machine learning, information retrieval as well as computational models of argument.  He obtained a diploma in law from the University of Augsburg, Germany, as well as a Master of Laws (LLM) and a Ph.D. in Intelligent Systems specializing in AI & Law under Prof. Kevin Ashley at the University of Pittsburgh.

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