How AI is transforming eDiscovery
- January 5, 2017
- by David Carns
Artificial Intelligence (AI) is impacting eDiscovery in ways that go well beyond TAR. So how is it set to help your firm work smarter?
Inspired applications of AI already touch many areas of our lives. Cars are using AI to learn how to drive themselves. Retail websites use it to suggest new products we might like. Photography software uses AI to accurately ID our photos based on who, or what, is in them. Facebook has even started trialing new AI-driven capabilities that can describe the content of photos to visually impaired users.
So it’s hardly surprising that AI is also continuing to impact eDiscovery in new ways. Of course, AI has already given birth to the whole field of Technology Assisted Review (TAR), leveraging machine learning techniques to revolutionize the document review process. But beyond TAR, AI is now helping litigators improve how they perform all sorts of vital tasks:
- Better understanding the data involved in legal matters and using that insight to drive a smarter eDiscovery process from the get-go
- Enhancing the document review management process and supporting legal teams to make the best use of review resources
- Empowering stakeholders to make quicker strategic decisions about legal matters, saving cost and delivering better business results
The need for speed
In an industry ruled by billable hours, speed is pivotal. AI can help legal teams fathom matter faster to really get under the skin of cases. That could mean unearthing which cast of characters is most important or which communication strands are the most revealing. Legal teams can then use these insights to craft better document review strategies and prioritize key players.
Making more intelligent connections
AI can also help review teams to find new and interesting areas of focus, going beyond what’s possible with traditional search terms and analytics to pull in a pool of new, information-rich documents. AI can look for documents similar to ones that legal teams have already focused on in review and identify important new documents that relate to those already identified during an offending event.
Optimizing the overall process
AI is set to improve the review management process itself, by automatically monitoring its progress and revealing things that humans would struggle to see. It can pinpoint the most effective reviewers without needing to run endless reports and uncover interesting patterns across large datasets, such as who has reviewed the most documents with the fewest overturned calls during the QC phase. AI can also perform some really unexpected functions like suggesting periods in the day that are most impactful for review and the least disruptive time to apply software improvements or system updates.
Constantly improving and inspiring
One of the great features of AI is that is that it continually refines itself, getting smarter as more data is reviewed. Because it’s omnipresent, the opportunities it has to learn are significant. Litigation teams are likely to get fired up by the new connections that AI will constantly reveal, leading to ever-more interesting discoveries. And ultimately, AI will allow legal and business decision-makers to not just pursue cases more successfully but also make intelligent strategic calls about how far to pursue a case. Or, indeed, about whether a case should be pursued at all.
Casepoint has been a true pioneer in the AI for eDiscovery arena. Learn more about how AI sits at the heart of our document review approach with CaseAssist and our latest and greatest evolution of TAR.