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Actos — Does New Federal Litigation Clarify Predictive Coding In eDiscovery?

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In Re: Actos (Pioglitazone) Products Liability Litigation recently surfaced as the newest case to fuel the continuing debate about the use of predictive coding technology in litigation. The plaintiffs allege a prescription drug for the treatment of type 2 diabetes called Actos increases the risk of bladder cancer in patients.

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On July 27, 2012, United States Magistrate Judge Hanna Doherty of the Western District of Louisiana entered a Case Management Order outlining the electronically stored information (ESI) protocol the parties must follow during discovery.

Central to the protocol is a detailed description of the predictive coding methodology the parties must utilize during discovery. Predictive coding is a type of machine-learning technology that enables a computer to help “predict” how documents should be classified based on limited training provided by their human counterparts. The technology is exciting for organizations attempting to manage skyrocketing legal budgets because predictive coding has the potential to save organizations millions in document review costs. That is because a computer can be used to help predict which documents within a large population of information are legally required to be produced to requesting parties during litigation. As a result, only a fraction of the documents that normally need to be manually reviewed by humans need to be reviewed. Supporters also believe this form of technology-assisted review is far faster and more accurate than paying attorneys to manually drudge through thousands or even millions of documents because computers don’t get tired or daydream.

Predictive coding technology is beginning to gain broader acceptance within the legal community as an alternative approach to the drudgery of page-by-page manual document review, but some have expressed reluctance. Part of the reason more attorneys haven’t embraced predictive coding technology is because although machine learning (the underlying technology behind predictive coding) has existed for decades, the technology is relatively new to the legal profession. Not surprisingly, early generation predictive coding tools are far more complex and difficult to use than traditional legal technology tools such as keyword search, concept search, email threading, and data clustering to name a few. Some feel asking attorneys to add predictive coding tools to their technology tool belt is like asking them to fly jet airplanes instead of drive cars. A jet airplane might be a faster and more efficient mode of transportation in many instances, but manning the cockpit without proper education and training could backfire.

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