End-to-end contract management company, Juro, has published a great new guide to machine learning in contracts, designed to be of use to everyone in the legal industry. The white paper has been written by Juro’s lead data scientist, Dr. Matthew Upson, and has been produced in partnership with Artificial Lawyer.
It looks at a range of issues and opportunities for using this technology and hopefully will answer many of the questions people have across the legal industry. You can find the guide here.
Richard Mabey, co-founder and CEO of Juro, commented:
‘AI has been part of our vision since we founded Juro in 2016, and we’ve seen more and more demand for AI-enabled products as the months go by. Sometimes clients have a clear understanding of the specific use cases for AI technologies, and the specific problems that they aim to solve with them. But we still see – understandably – some confusion among in-house lawyers around when and why investment in AI-enabled platforms makes sense.
Our core data science team of Dr. Matt Upson, who was the first to ship an ML model into production for the UK Government, and Aleksej Ermolaev, our machine learning engineer, have spent a year exploring, building and deploying machine learning models for contracts and more importantly looking at the problems AI can (and cannot) solve.
In this whitepaper, produced in partnership with Artificial Lawyer, Matt explores what’s real and what’s possible, as well as defining all the key terms in machine learning and talking through the practical implications of these breakthroughs for legal. We hope you find it interesting – download your copy here.’
- Jargon buster: key terms
- Machine learning defined: training and inference/prediction
- Machine learning fields relevant in legal
- Exploring the data types in contracts: which are usable?
- What is deep learning?
- Tech giants circle legal: what happens next?
- And more…