In late September Bloomberg Law announced several new research features which leverage artificial intelligence and machine learning technologies to accelerate case law research. The The new “Points of Law” feature allows attorneys to quickly find language critical to a court’s reasoning to support their legal arguments . This feature was immediately available to all current subscibers to Bloomberg Law at no additional cost.
The Bloomberg Law platform now features one million points of law and is updated throughout the day. “Points of law” results are generated by the application of machine learning to the Blaw database of 13 million published and unpublished state and federal court opinions. Researchers can either start there research with a point of law or start with a keyword then sort by relevance or most cited.
This new feature was created is response to the market demand for workflow enhancing tools. “Points of law” research results highlight the relevant language in each opinion. The press release describes the benefit as “enabling attorneys to shorten their research time and quickly identify the best language to strengthen legal arguments.”
Points of Law From a case, users can navigate seamlessly among points of law and can also augment their research with related points of law and with relevant citing cases shown as a list or an interactive timeline via the Citation Map feature.
The Citation Map provides a visualization of most cited cases, relationships among key cases, and changes over time for the point of law at issue. This is a radical departure from traditional notions of a citator.
Search and Filter The system also supports familiar search techniques for narrowing focus including keyword search and jurisdictional filters.
“Points of Law is another example of our commitment to continuous innovation and ongoing investment in data and technology to empower attorneys to more effectively and efficiently advise their clients,” said Scott Mozarsky, President, Bloomberg Law. “With Points of Law, we have streamlined and improved the legal research process using machine learning and data visualization to reveal previously undiscoverable patterns and insights.
A Few Suggestions. During a recent demo, I found the Point of Law Results somewhat overwhelming. Maybe it is my “mature” eye issues – but I think that my experience of the results would benefit from some color variation or a word cloud to help with sorting and focusing within results.
There is no doubt the legal research is is a state of continuous reinvention. My natural bias is rooted in nested topical hierarchies until I have the “a ha” moment when I finally “get” the benefit of a radically new display. But I have to also admit that Points of Law was not created for me – it was created for the generation of lawyers who grew up clutching a Gameboy and have a natural orientation to digital displays of information.
While Points of Law could be viewed as a response to the Thomson Reuters “granddaddy” of legal headnotes systems, a look at the product evokes similarities to more recent startups: Fastcase (timelines), Ravel Law (citation “constellations”) and CARA (explanatory parentheticals). But of course, Bloomberg is adding their own unique twist, rendering, reorganization, reimagining… of an old problem – determining the best authority to support your case and applying AI and Machine Learning to produce a reimagined user experience and workflow.
It is important to note that Bloomberg is still supporting more traditional headnotes and classification systems in their BNA Libraries on Bloomberg Law. It will be interesting to see when and if these classification systems are intergrated with the new AI generated points of law.
The White Paper To demonstrate the power of Points of Law in conducting case law research on complex, evolving issues, Bloomberg Law developed a new white paper, examining the antitrust law implications of pharmaceutical industry patent disputes. To download the report, visit http://on.bna.com/ywrF30foY4t.