In Part One of “How Good is Your Predictive Coding Poker Face?” we shared video footage of Maura R. Grossman, Craig Ball, Ralph C. Losey and myself (Matthew Nelson) discussing similarities between predictive coding technology and the popular poker game Texas Hold ‘em during a panel discussion at Legal Tech New York in January. In particular we discussed how to “read your opponent” when devising predictive coding protocols and we tackled sensitive issues like whether or not parties should be required to show their “discard pile” (aka non-responsive files used to train the predictive coding system) to the other side.
In Part Two of our two part video series, the panel digs deeper into the parallels between poker and predictive coding by discussing a “middle ground” approach to predictive coding referred to as “splitting the pot.” The panel also explores interesting issues like the dwindling role of keyword search technology in eDiscovery, the importance of statistics, and the need for transparency. Listen in as the panel discusses these and other important eDiscovery issues and feel free to share your feedback.
Does “splitting the pot” make sense?
In poker, two or more players might end up splitting the money (the pot) when they have the same hand. In this situation, neither party wins the hand, but neither party loses. Instead, they live to play another day. Listen to the panelists explore how transparency could be the key to a “middle ground” approach where neither party completely wins the discard pile issue, but neither party loses. The panel also discusses the role judges or special masters can play in ensuring a fair protocol without sacrificing traditional notions of privilege.
Does using keyword search in conjunction with predictive coding tools result in a stacked deck?
Some predictive coding advocates believe keyword search is dying a slow death in eDiscovery while others believe the proper application of keyword searching has simply changed. When should keyword searches be used in conjunction with predictive coding technology, if at all? Is the deck stacked against parties that insist on keyword culling prior to using predictive coding technologies? Should other technology tools in the litigator’s technology toolbelt be incorporated into predictive coding protocols? Hear from Ralph Losey about a case where keyword searching tools didn’t quite stack up to predictive coding technology and listen to Maura Grossman explain how the high cost of many predictive coding solutions can slow adoption of better technology approaches.
Will ignoring statistics and transparency ruin your game?
Every good poker player understands the important role statistics play when making decisions like how much you should bet or whether or not you should call your opponent’s bet. Basic statistical calculations can help players estimate the likelihood of beating their opponent in certain situations, but miscalculations or ignoring statistics completely can result in costly errors. Listen to Maura Grossman discuss basic statistical approaches that can make or break your predictive coding protocol and hear Craig Ball’s final word on the importance of transparency for both parties.
You may not understand everything there is to know about predictive coding technology after watching these short video clips. However, you will receive valuable tips from industry experts to help you avoid playing a rigged game with a stacked deck. Or as Kenny Rogers might say, you will know when to walk away from a bad predictive coding game and you will know when to run.