Design, Transparency, and Big Data in Civil Litigation

Electronic discovery has transformed the way cases are litigated. Gone are the days of manual review, where litigators spent days poring over emails, messages, and documents. Today’s e-discovery technologies mine through vast troves of information, looking for the needle in the proverbial haystack that will blow a case wide open. But these same litigators are now skeptical of the results machines can deliver, and are reluctant to rely on them without peering under the covers. To address this, we need to help lawyers think about numbers and certainty. We need to ease them into concepts like false positives and false negatives. Without overwhelming them, we need to show them how the whole process works. This is, above all, a design problem.

In this session, we’ll describe how we designed a novel technology-assisted review platform for Daegis. It blends modern machine learning and Hadoop Map/Reduce algorithms with minimal input from human reviewers. Importantly, our process continuously estimates the precision and recall of the review process and displays relevant information in a dashboard designed for statistical novices (e.g., attorneys) and savants (e.g., expert witnesses) alike.

Photo of Dean Malmgren

Dean Malmgren

Datascope Analytics

Dean Malmgren is co-founder and managing partner of Datascope Analytics. As an author of several peer-reviewed publications on big data analytics and visualization, Dean is excited about bringing cutting-edge techniques out of research and into practice. When not teasing himself or others, Dean can be found swimming, cycling, or running for silly long distances. Dean received a BS in math and chemical engineering from the University of Michigan and a PhD in chemical engineering from Northwestern University.

Photo of Mike Stringer

Mike Stringer

Datascope Analytics

Mike Stringer is co-founder and managing partner of Datascope Analytics. A physicist gone wild, Mike is passionate about realizing the potential for big data analytics to make a positive impact on business and society. Despite wearing a suit occasionally, he still finds the time to argue with others about Bayesian statistics, explore the amazing food in Chicago, and has recently become fascinated with typography. Mike received a BS in Engineering Physics from the University of Colorado and a PhD in physics from Northwestern University.


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