Predictive Analytics and Artificial Intelligence… Science Fiction or E-Discovery Truth?

Predictive Analytics, Machine Learning, Predictive Coding, Automated Coding or what ever the buzz word of the moment may be… non-linear computer assisted or automated review is the new “it” topic in the E-Discovery space and not likely to disappear any time soon. The industry would have you believe that this cutting edge breakthrough is game changing and will revolutionize the world as you know it. In many ways this has changed the landscape of the E-Discovery space, rendering the tried and true Electronic Discovery Reference Model (EDRM) inadequate to encompass the nuances of the changing workflows that have emerged as a result. But, somewhere lost in the discussion of cutting edge algorithms and lambda calculus is one important fact; none of this is novel and it is being used all around us every day in medical diagnostics, customer relationship management (CRM) tools, insurance, telecommunication and even your personal credit score.

Predictive Analytics Take out Some of the Guess Work

Predictive analytics as applied to E-Discovery may not be the silver bullet some companies have been touting, but if adapted and properly managed as it has been in other industries it could rein in the cost, time and labor that has rendered litigation almost cost prohibitive. The seminal text on predictive analytics, (then called Exploratory Data Analysis) was published over three decades ago[1] and although it has had multiple applications since the first publication, the core tenets have remained the same. Instead of following data collection with an artificially imposed model based on case assumptions or best guesses and then trudging through the output page by page manually, the process begins with analyzing the sample of data with the goal of inferring which model or algorithm is most appropriate. That model is then refined with new parameters as more of the data is analyzed or rules are refined to the point that the model reaches maximum accuracy and can run with minimal or no supervision throughout the body of data.

Continue reading “Predictive Analytics and Artificial Intelligence… Science Fiction or E-Discovery Truth?” »