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The use of predictive coding in e-discovery answers the need to automate document review for discovery purposes. Why is automation of this process now so necessary? Because Big Data is upon us, and the legal profession is as much affected by this mountain of information as is business. We need automation to make our way through this.
Prediction coding is one part of the process of quantitative predictive analytics, and the use of predictive analytics in the practice of law is charging well past its role in e-discovery. Think about it: how often is a lawyer required to make a prediction: Do I have a case? What is our likely exposure? How should this legal matter be priced? Who in the firm is best equipped to handle it? What's up with the judge? What's the best jury composition? These are the questions that can, and will, rely on human-trained technology designed to wrest these decisions from the frailties of human thinking.
Why is it that those who are best skilled at advocating for others are ill-equipped at advocating for their own skills and what to do about it?
There is no efficient market for the sale of bankruptcy assets. Inefficient markets yield a transactional drag, potentially dampening the ability of debtors and trustees to maximize value for creditors. This article identifies ways in which investors may more easily discover bankruptcy asset sales.
The DOJ's Criminal Division issued three declinations since the issuance of the revised CEP a year ago. Review of these cases gives insight into DOJ's implementation of the new policy in practice.
Active reading comprises many daily tasks lawyers engage in, including highlighting, annotating, note taking, comparing and searching texts. It demands more than flipping or turning pages.
With trillions of dollars to keep watch over, the last thing we need is the distraction of costly litigation brought on by patent assertion entities (PAEs or "patent trolls"), companies that don't make any products but instead seek royalties by asserting their patents against those who do make products.