Jennifer Swanton, Shannon Capone Kirk, and John Del Piero: [PART TWO] Analytics and Predictive Coding Technology for Corporate Attorneys: Six Use Cases

Extract from Jennifer Swanton, Shannon Capone Kirk, and John Del Piero’s article “Analytics and Predictive Coding Technology for Corporate Attorneys: Six Use Cases”

This is the second article in a two-part series, designed to help create a better relationship between corporate attorneys and advanced technology. In our first article, we worked to demystify the language technology providers tend to use around AI and analytics technology.

With the terminology now defined, we will now focus on six specific ways that corporate legal teams can put this type of technology to work in the e-discovery and compliance space to improve cost, outcome, efficiencies.

1. Document Review and Data Prioritization: The earliest example of how to maximize the value of analytics in e-discovery was the introduction of TAR (technology-assisted review). CAL (or continuous active learning) allows counsel to see the most likely to be relevant documents much earlier on in the process than if they had been simply looking at search term results, which are not categorized or prioritized and are often overbroad. Plainly put, it is the difference between an organized review and a disorganized review.

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