For at least two decades, artificial intelligence has been used in e-discovery to help surface and prioritize review of potentially responsive documents from large document collections. But while technology-assisted review (TAR) has traditionally been driven by AI in the form of supervised machine learning, some vendors and e-discovery professionals are starting to experiment with the use of generative AI in its place. 

So how effective is generative AI for document review in e-discovery? Is it a replacement for traditional TAR or a supplement? Are there other ways in which this rapidly evolving technology can be used in discovery? 

On this week’s LawNext, we are discussing the application of generative AI in e-discovery. To do so, host Bob Ambrogi is joined by three computer and data scientists from Redgrave Data, a consulting firm that specializes in e-discovery and data science. Today’s guests are:

• Dave Lewis, chief scientific officer, who has over three decades of experience in AI and statistics.

• Lenora Gray, data scientist, who has worked for more than 15 years in law firm project management and matter support roles.

• Jeremy Pickens, head of applied science, a pioneer in the fields of collaborative exploratory search and technology assisted review. 

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• Paradigm, home to the practice management platforms PracticePanther, Bill4Time, MerusCase and LollyLaw; the e-payments platform Headnote; and the legal accounting software TrustBooks.

 

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