Tomorrow I will be speaking on the opening panel at the Advanced E-Discovery Institute @ Georgetown Law. The event draws hundreds of lawyers and technologists to Washington DC to discuss the latest advances in the rapidly evolving field of E-Discovery.
LexPredict is an enterprise legal technology and consulting firm, specializing in the application of best-in-class processes and technologies from the technology, financial services, and logistics industries to the practice of law, compliance, insurance, and risk management.
We focus on the goals of prediction, optimization, and risk management to enable holistic organizational changes that empower legal decision-making. These changes span people and processes, software and data, and execution and education.
Yesterday I had the pleasure of participating in the Thomson Reuters Law Firm COO & CFO Forum Pre-Conference Workshop on Big Data. The half day workshop explored various way that law firms and outside counsel can use data to be better lawyers and run better businesses.
Here is the information for my panel (below) and the full program is located here.
“Organized by Wolters Kluwer and Inkietos, and under the honorary presidency of His Majesty Felipe VI, the Legal Management Forum aims to serve as a space for reflection and knowledge of the main challenges and opportunities related to management in the legal profession.”
The global legal innovation conversation is growing and it was my pleasure to deliver the keynote address to the more than 400 in attendance here in Madrid.
Perhaps some hyperbolic language in here but the basic idea is still intact … for law+economics / empirical legal studies – the causal inference versus machine learning point is expressed in detail in this paper called “Quantitative Legal Prediction.” Mike Bommarito and I have made this point in these slides, these slides, these slides, etc. Mike and I also make this point on Day 1 of our Legal Analytics Class (which really could be called “machine learning for lawyers”).