Christina Ling, Everlaw: Predictive Coding in the World of Ediscovery

Extract from Christina Ling’s article “Predictive Coding in the World of Ediscovery”

The human brain is continually being fed heaps of sensory information that must be processed and acted upon quickly. One way to significantly improve this process is to predict incoming information based upon previous experience. The projected information can be processed efficiently, and anything unexpected can be dealt with accordingly. This is the concept behind predictive coding.

The Connection Between Predictive Coding, Artificial Intelligence, and Ediscovery

In the context of ediscovery, predictive coding is a type of computer-assisted review (CAR), also known as Technology-Assisted Review (TAR), that uses artificial intelligence to categorize documents based on a sample set of documents. This process can dramatically drill down the number of documents in extensive collections to include only those relevant to a specific matter.

Artificial intelligence (AI) gives a computer the ability to perform tasks that were previously completed by humans. Predictive coding uses AI to automate these manual tasks, an increasingly valuable function, considering the massive amount of data currently being generated during the ediscovery process. When powered by AI, ediscovery becomes a more frictionless process — allowing legal teams to get a handle on the facts of a case with greater speed, efficiency, and accuracy at a much lower cost. 

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