As many translators question the future in view of the rise of machine learning, and in the legal domain in particular due to concerns about quality, confidentiality, and reliability of translations, I noted with interest a presentation about legal analytics, and how big data and machine learning is being applied to the tasks that lawyers undertake.
Applications include: quantitative legal prediction – for example of trial outcomes and to assist in negotiations; automated contract extraction; or seeking market opportunities.
The SlideShare presentation, by Professor Daniel M. Katz¹ and Professor Michael J. Bommarito II², suggests that Machine Learning as a Service (MLaaS) is ‘the next big thing’, hand in hand with Open Source, and provides an insightful overview of changes in the legal market.
By the way, for those of you who don’t fear a bit of maths & stats, Professor Katz has an introductory class online (currently in beta) called ‘Quantitative Methods for Lawyers‘ (free access), as well as a Legal Analytics Course that aims to train people to “efficiently manage, collect, explore, analyze, and communicate in a legal profession that is increasingly being driven by data“.
¹ In 2014, Professor Katz joined the external affiliated faculty at CodeX – The Stanford Center for Legal Informatics. In addition to teaching and researching, he serves as an editor of the International Journal of Law and Information Technology (Oxford University Press) and as a member of the Editorial Board of the Journal of Artificial Intelligence & Law (Springer Scientific). He serves on the Editorial Advisory Board for Law Technology News and is a member of the American Bar Association Task Force on Big Data and the Law.
² Professor Bommarito is Adjunct Professor of Law and Head of Research at Reinvent Law Laboratory, Michigan State University College of Law. He founds, builds, consults for, operates, and advises financial services and legal services startups and businesses, publishes widely in law reviews and scientific journals, and his work has been highlighted in a number of media outlets such as New York Times, Wired, Vox, Slate Magazine, Huffington Post and ABA Journal.