eDiscovery expert Dr. Bill Dimm explains why some performance metrics don’t give an accurate view of performance for eDiscovery purposes, and why that makes a lot of research utilizing such metrics irrelevant for eDiscovery.
TAR vs. Keyword Search Challenge, Round 5 (Bill Dimm)
In this fifth round of Bill Dimm’s TAR vs. Keyword Search Challenge, TAR beat the keyword searches by a huge margin.
United’s AI-Doc Review Snafu Leads to Discovery Extension
United gave the passengers more than 3.5 million “core” documents during discovery. But only about 600,000—17 percent— of the documents were responsive to the passengers’ discovery requests.
Relatively Speaking: Predictive Coding Technologies and Protocols Survey Results
The Predictive Coding Technologies and Protocols Survey is a non-scientific survey designed to help provide a general understanding of the use of predictive coding technologies and protocols from data discovery and legal discovery professionals within the eDiscovery ecosystem.
A Leap Forward for the Recognized Use of AI and Predictive Coding in Insolvency Trials and Investigations
Technology-Assisted Review is being used increasingly and, combined with recently-proposed changes to the English disclosure regime, could result in more legal cases becoming economically viable to fight and lead to greater recoveries for creditors.
TAR vs. Keyword Search Challenge, Round 3 (Bill Dimm)
During this iteration of the TAR vs. Keyword Search Challenge held at the Education Hub at ILTACON 2018, TAR won across the board, as in previous iterations of the challenge.
Predictive Coding Technologies and Protocols: Overview and Survey
With the growing awareness and use of predictive coding in the legal arena today, it appears that it is increasingly more important for electronic discovery professionals to have a general understanding of the technologies that may be implemented in electronic discovery platforms to facilitate predictive coding of electronically stored information.
TAR, Proportionality, and Bad Algorithms (1-NN)
Are lawyers who use platforms lacking a simple tweak of a bad algorithm committing malpractice by doing so?
The Importance of Contextual Diversity in Technology Assisted Review
Contextual diversity refers to documents that are different from the ones already seen and judged by human reviewers. The contextual diversity algorithm identifies documents based on how significant and how different they are from the ones already seen and then selects training documents that are the most representative of those unseen topics for human review.
Stop Worrying and Learn to Love Technology-Assisted Review (Part Two)
TAR is not meant to replace standard review processes and protocols, but instead to help streamline those processes so that review can be more targeted, fruitful and efficient.