Toby was kind enough to highlight for me a very interesting conference scheduled for April 15 at Berkeley Law School. It’s called the New and Emerging Legal Infrastructures Conference (NELIC), and is hosted by a legal startup called Robot Robot & Hwang — two of the partners are ‘robots’; the third is Tim Hwang, formerly a researcher at the Berkman Center for Internet and Society at Harvard, and currently a strategist and analyst at The Barbarian Group.

The firm’s mission is “to marshall a universe of thinking from the world of technology, startup, and computational science to bear on the often staid and conservative world of legal practice.” And the sessions for the conference dovetail nicely with this:
  • Quantitive Legal Prediction: “How might recent work in machine learning and natural language processing influence legal practice and strategy in a big way? To what extent can judicial and legal decision-making be reduced to statistical modeling and prediction?”
  • Legal Automation: “What is the current state of the automation of legal tasks, and how far can it scale? How much can be replaced by these applications, and what does the legal profession look like in a world of broad automation and commodification?”
  • Legal User Experience and Interface Design: “The design of easy-to-use ‘human-readable’ user interfaces to manage complex legal tasks holds the possibility of radically democratizing access to the legal system. What is the broad impact of abstracting from legal text? What are the best practices in the design of these interfaces?”
  • Legal Finance: “As banks and other firms continue to experiment with the finance and investment of lawsuits, what is the long-term impact on the legal marketplace? Could it open the door to securitization and larger tradable legal assets? What would be the opportunities? The risks?”
A pretty interesting line-up, and a varied set of speakers as well. I’m scheduled to speak as part of the Legal Automation session, and will try to blog about as much of the conference as I can.