Not only that, but it has done so for nearly a year now, which I just discovered a couple of days ago.  In August 2019, the American Bar Association adopted Resolution 112, which “urges” courts and lawyers to address Artificial Intelligence (AI).

Specifically, Resolution 112 (available here) “urges courts and lawyers to address the emerging ethical and legal issues related to the usage of artificial intelligence (AI) in the practice of law including: (1) bias, explainability, and transparency of automated decisions made by AI; (2) ethical and beneficial usage of AI; and (3) controls and oversight of AI and the vendors that provide AI.”

Since Judge Andrew Peck’s decision in Da Silva Moore v. Publicis Groupe in February 2012, courts have recognized “that computer-assisted review is an acceptable way to search for relevant ESI in appropriate cases”.  We’ve seen numerous courts reinforce that decision by approving the use of Technology Assisted Review (TAR) or predictive coding (which uses AI) in their courts as well when the issue has been brought before them.  Many people use the terms “TAR” and “predictive coding” interchangeably, though many others consider TAR to be much more than just predictive coding, encompassing clustering, near-dupe identification and other computer assisted technologies as well.  Regardless of your term preference, court approval of the technology has been in place for over eight years now.  Eight years!  And, it is recognized by many to save considerable costs in document review while producing results that are at least as good as (and in many cases, better than) manual document review.

Still, the adoption of predictive coding has been slow.  As recently as the 2018 ABA Legal Technology Survey Report (released in early 2019), only “12% {of lawyers responding to the survey} report using predictive coding to process or review e-discovery materials”, while the “primary tool used to review e-discovery materials remains keyword searching” at 80% (which was “up significantly” from the previous year’s survey).  So, the legal community is a long way from embracing one form of AI that has been court-accepted for over eight years – imagine how long it will take to embrace AI in other areas of law.

Yet, many (if not most) of you are already using AI in your daily lives.  Do you have an Amazon Echo device or an iPhone?  If so, you’re probably communicating with “Alexa” or “Siri”, which are using a neural network and natural language processing to communicate with you.

What’s your understanding and knowledge of AI?  Do you understand what an algorithm is?  Do you know the difference between supervised and unsupervised learning and which category predictive coding falls into?  Do you know what reinforcement learning is?  Or transfer learning?  Or deep learning?

Here’s a link to an article from a few years ago that defines these and other terms – it’s at least a good start.  Soon, I’ll write a follow up post with links to other resources that help people better understand AI and current uses of it in legal and eDiscovery contexts – there are several good ones from over the years I’ve already written about, but I want to review that list and supplement it.  Better yet, if you’re aware of any good resources that explain AI and predictive coding, feel free to note them in the comments below.  Let’s crowdsource this thing!

So, what do you think?  Have you ever used predictive coding on a case to conduct document review?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by my employer, my partners or my clients. eDiscovery Today is made available solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscovery Today should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.