Proportionality Analysis Defeats Motion for Forensic Examination

May 28, 2018

It is rare of a judge to change their mind after making a decision. It is rarer still for a judge to celebrate doing so in a written opinion for the world to see. But that is exactly what Magistrate Judge Jeffrey Cole has done in his opinion dated May 17, 2018 in Motorola Sols., Inc v. Hytera Communications Corp., No. 17 C 1973 (N.D. Ill.).

This celebration is one reason that Judge Cole’s Order denying Motorola’s motion for forensic inspection is so remarkable. Another is that it begins with a quote, a rare occurrence in judicial orders, one that I always like. The quote celebrates the better late than never philosophy of changing your mind to follow a new understanding, a personal wisdom. The quote is by the late, great Supreme Court Justice, Felix Frankfurter. Felix served as a judge on the Supreme Court from 1939 to 1962.  Before that he was, among other things, a Harvard Law Professor and co-founder of the American Civil Liberties Union. Here is the quote with which Cole begins his order:

“Wisdom too often never comes, and so one ought not to reject it merely because it comes late.”

Henslee v. Union Planters Nat. Bank & Trust Co., 335 U.S. 595, 600, 69 S. Ct. 290, 93 L. Ed. 259, 1949-1 C.B. 223 (1949)

(Frankfurter, J., dissenting)

Another unusual thing about Judge Cole’s order, and the real reason I am writing about it, is that the wisdom that came to him was from the doctrine of proportionality and Rule 26(b)(1). This was the basis for Judge Cole to deny plaintiff’s motion for a forensic inspection of defendant’s computers, in China no less.

District Court Judge Ronald Norgle had previously allowed the parties until October 6, 2017, to conduct discovery on the statute of limitations defense only and stayed all other discovery. The parties had one month in which to take discovery on a very limited topic of fraudulent concealment, which is a type of tolling within the doctrine of equitable estoppel of the limitations defense. Nothing else. After all, Motorola has waited almost ten years before filing a trade-secret theft suit against a Chinese corporation for allegedly stealing its radio wave technology. As Judge Cole colorfully described the situation (citations to record removed in all quotes) with a reference to Hannibal:

While the inquiry should have been uncomplicated, it has become a long, drawn out, pitched battle — one, in a rhetorical sense, to rival the Punic Wars — albeit without the elephants and the Alps and the sheer drama.

After that, the parties exchanged motions to compel repeatedly. Deadlines were extended, from one month to several. Thousands of pages of memoranda and exhibits were filed. 1  And, again, this was all over the supposedly limited discovery on a limited topic that ought to have taken little time and effort. The very nature of what occurred tends to sustain the all too prevalent observation that discovery has become more important than the actual case. Bell Atl. Corp. v. Twombly, 550 U.S. 544, 595, n.13, 127 S. Ct. 1955, 167 L. Ed. 2d 929 (2007); A.H. Robins Co. v. Piccinin, 788 F.2d 994, 1013 (4th Cir. 1986).

1 The filings and orders in this case which, again, is only in the preliminary stage of determining whether Motorola’s filing is timely, already cover more than 7,500 pages. See also n. 5, infra.

Five months into this “limited” discovery process Motorola asked to conduct a forensic examination of the computers of “key Hytera witnesses who have been involved in the use of Motorola’s confidential information and any relevant Hytera servers … on which Hytera has stored Motorola documents,” all of which are located in China. Motorola said it wanted to “begin with forensic inspection of the computers” of seven Hytera employees. Judge Cole said this request reminded him of Winston Churchill’s famous quip: “Now this is not the end. It is not even the beginning of the end.”

Flip Flopping Towards Wisdom

After several hearings Judge Cole was persuaded by the siren songs of plaintiff’s counsel from the well-known firm of Kirkland & Ellis LLP. They must have been very good orators and put on a compelling argument to support their motion. They convinced Judge Cole to allow them to begin a forensic examination process in China under elaborate Hague Convention procedures. Only after the hearings and oral decision to compel the inspection did Judge Cole realize the error of that decision. Judge Cole to his credit does not blame Kirkland and Ellis litigators for leading him astray. Following standard judicial protocol Judge Cole assumed full responsibility for the initial error:

Over the course of two lengthy hearings on March 21 and April 4, 2018, I tentatively concluded that forensic examination of Hytera’s computers would be appropriate, but only if the parties could arrive at a suitable protocol that would not, among other things, run afoul of Chinese law. As we discuss, infra at 5, that was a mistake. But the law frowns on relying on a blunder to gain an opportunistic advantage. Cf. Architectural Metal Systems, Inc. v. Consolidated Systems, Inc., 58 F.3d 1227, 1231 (7th Cir.1995); Market Street Associates; Packer Trading Co. v. CFTC, 972 F.2d 144, 150 (7th Cir 1992); Centex Construction v. James, 374 F.2d 921, 923 (8th Cir.1967). 2

2 We should not be understood as ascribing fault to plaintiff’s counsel. After all, in our adversary system, lawyers properly play a partisan role. Masias v. Secretary of Health and Human Svcs, 2009 U.S. Claims LEXIS 281, at *27 (Fed. Cl. 2009); Philips Medical Systems Intern. B.V. v. Bruetman, 8 F.3d 600, 606 (7th Cir.1993) (Posner, J.). See also Smith v. Robbins, 528 U.S. 259, 293, 120 S. Ct. 746, 145 L. Ed. 2d 756 (2000) (Souter, J., dissenting) (“a partisan scrutiny of the record and assessment of potential issues, goes to the irreducible core of the lawyer’s obligation to a litigant in an adversary system … .”). Mistakes are ultimately (and in most cases) the responsibility of the court.

Judge Cole went on to celebrate a jurists right to change their mind in order to get things right.

The scope of discovery that I was initially inclined to allow was, in the context of the present inquiry that had been narrowed by the district court to the limitations issue, overbroad. What is being sought goes beyond the issue of equitable tolling. In the end, Motorola’s counsel and I were talking about relevance to allegations in Motorola’s complaint. And so, well beyond the statute of limitations, by the end of the April 4 hearing, discovery was encompassing documents related to Motorola’s entire case.

As we have said, “all judges make mistakes,” Fujisawa Pharm. Co., 115 F.3d at 1339, and, when possible, it is best that judges put them right.

Proportionality Applied to Restrain Discovery

In the May 17, 2018 order Judge Cole found the wisdom to say no and forbid the forensic examination of the computers in China. He did so because he found that this discovery was “out of proportion with the needs of this case, as presently limited by the district court” and cited Rule 26 (b)(1), Federal Rules of Civil Procedure. Although I am sure that he heard extensive argument and evidence concerning the estimated costs and burdens imposed by the forensic exams, his decision did not focus on costs. Instead it focused on one of the other very important factors in 26(b)(1), “the importance of the discovery in resolving the issues.” Judge Cole realized that the computers in China could not possibly have information in them of any real relevance to equitable tolling of the statute of limitations defense.

At a minimum, even if relevant to the present limited issue, discovery of computers in China is not proportional to the importance of discovery in resolving the issues and the burden and expense of the proposed discovery manifestly outweighs its likely benefit to the very limited question of equitable tolling. Although the federal discovery rules are permissive, they are not, as Judge Moran wisely put it, “a ticket to an unlimited … exploration of every conceivable matter that captures an attorney’s interest.” Sapia v. Bd. of Educ. of the City of Chi., 2017 U.S. Dist. LEXIS 73153, 2017 WL 2060344, at *2 (N.D. Ill. 2017); see also Leibovitch v. Islamic Republic of Iran, 2018 U.S. Dist. LEXIS 31713, 2018 WL 1072567, at *11 (N.D. Ill. 2018). “[J]udges should not hesitate to exercise appropriate control over the discovery process.” Herbert v. Lando, 441 U.S. 153, 177, 99 S. Ct. 1635, 60 L. Ed. 2d 115 (1979). Failure to exercise that control results in needless and enormous costs to the litigants and to the due administration of justice.

Judge Cole also understood that a forensic inspection is a drastic remedy that requires good cause not shown by plaintiff here:

The original idea here was for a month or so of discovery focused on the very limited issue of the statute of limitations. While it is rare for parties to complete discovery even by dates chosen by their counsel, there can be no dispute that things have already gone far beyond what was intended and what was necessary in the statute of limitations portion of this case, in terms of time and scope. Now, Motorola wants things to go very much further. Forensic examination is generally regarded as a drastic step even in general discovery. See, e.g.,John B. v. Goetz, 531 F.3d 448, 460 (6th Cir. 2008) (“mere skepticism that an opposing party has not produced all relevant information is not sufficient to warrant drastic electronic discovery measures.”). As the court said in In re Ford Motor Company, 345 F.3d 1315 (11th Cir. 2003):

““In the absence of a strong showing that the responding party has somehow defaulted in this obligation, the court should not resort to extreme, expensive, or extraordinary means to guarantee compliance. Forensic inspection of computer hard drives is an expensive process, and adds to the burden of litigation for both parties, as an examination of a hard drive by an expert automatically triggers the retention of an expert by the responding party for the same purpose. Furthermore, examination of a hard drive inevitably results in the production of massive amounts of irrelevant, and perhaps privileged, information … . This court is therefore loathe to sanction intrusive examination of an opponent’s computer as a matter of course, or on the mere suspicion that the opponent may be withholding discoverable information.”

The Advisory Committee Notes to Rule 34 recognize that courts must use caution in evaluating requests to inspect an opposing party’s electronic devices or systems for ESI, in order to avoid unduly impinging on a party’s privacy interests:

Inspection or testing of certain types of electronically stored information or of a responding party’s electronic information system may raise issues of confidentiality or privacy. The addition of testing and sampling to Rule 34(a) with regard to documents and electronically stored information is not meant to create a routine right of direct access to a party’s electronic information system, although such access might be justified in some circumstances. Courts should guard against undue intrusiveness resulting from inspecting or testing such systems.

Fed. R. Civ. P. 34, Advisory Committee Notes—2006 Amendment (emphasis added). Likewise, the Sedona Principles urge general caution in this area:

Civil litigation should not be approached as if information systems were crime scenes that justify forensic investigation at every opportunity to identify and preserve every detail … . [M]aking forensic image backups of computers is only the first step of an expensive, complex, and difficult process of data analysis that can divert litigation into side issues and satellite disputes involving the interpretation of potentially ambiguous forensic evidence.

The Sedona Principles, supra, at 34, 47. 4

Conclusion

Judge Cole’s wrap up is wise and witty and something you may want to quote in many discovery disputes, especially the footnote:

Parties are entitled to a reasonable opportunity to investigate the relevant facts — and no more. Upjohn Company v. United States, 449 U.S. 383, 390, 101 S. Ct. 677, 66 L. Ed. 2d 584 (1981); Vakharia v. Swedish Covenant Hosp., 1994 U.S. Dist. LEXIS 2712, at *2 (N.D. Ill. 1994) (Moran, J.). Motorola has already had that reasonable opportunity and far more. What was intended to be a month-long process of discovery on a very limited issue has turned into a protracted affair in which Motorola has received 700,000 documents — nearly 3 million pages — over a period of eight months. 5

5 A ream of paper is 500 sheets, which is 2 inches tall. Three million pages is 6,000 reams, meaning that 3 million pages of discovery, which is about 1,000 feet high or 100 stories high. By any measure, that is extraordinary.

Yet, apparently for Motorola, it’s not enough. It now wants a forensic inspection of several computers in China — and it warns that that is only the “beginning.” What should have been limited discovery on a “straightforward [issue has] spiral[ed] out of control.” Montanez v. Simon, 755 F.3d 547, 552 (7th Cir. 2014). The time has come to say: “enough is enough.” Walker v. Sheahan, 526 F.3d 973, 981 (7th Cir. 2008). Eight months of “limited,” single-issue discovery are now at an end. Motorola’s motion for forensic inspection is denied.

Enough is enough. To go further would have been a disproportionate burden, especially considering the very narrow issue allowed in discovery. Judge Cole at first made a mistake, and then he changed his mind and made it right. He is a wise judge. I wish there were more like him. Except of course if you change your mind to rule against me! <‘_’>


e-Discovery and Poetry on a Rainy Night in Portugal

April 17, 2018

From time to time I like read poetry. Lately it has been the poetry of Billy Collins, a neighbor and famous friend. (He was the Poet Laureate of the United States from 2001 to 2003.) I have been reading his latest book recently, The Rain in Portugal. Billy’s comedic touches balance the heavy parts. Brilliant poet. I selected one poem from this book to write about here, The Five Spot, 1964. It has a couple of obvious e-discovery parallels. It also mentions a musician I had never heard of before, Roland Kirk, who was a genius at musical multi-tasking. Enjoy the poem and videos that follow. There is even a lesson here on e-discovery.

The Five Spot, 1964

There’s always a lesson to be learned
whether in a hotel bar
or over tea in a teahouse,
no matter which way it goes,
for you or against,
what you want to hear or what you don’t.

Seeing Roland Kirk, for example,
with two then three saxophones
in his mouth at once
and a kazoo, no less,
hanging from his neck at the ready.

Even in my youth I saw this
not as a lesson in keeping busy
with one thing or another,
but as a joyous impossible lesson
in how to do it all at once,

pleasing and displeasing yourself
with harmony here and discord there.
But what else did I know
as the waitress lit the candle
on my round table in the dark?
What did I know about anything?

Billy Collins

The famous musician in this poem is Rahsaan Roland Kirk (August 7, 1935[2] – December 5, 1977). Kirk was an American jazz multi-instrumentalist who played tenor saxophone, flute, and many other instruments. He was renowned for his onstage vitality, during which virtuoso improvisation was accompanied by comic banter, political ranting, and, as mentioned, the astounding ability to simultaneously play several musical instruments.

Here is a video of Roland Kirk with his intense multimodal approach to music.

One more Kirk video. What a character.

____

The Law

There are a few statements in Billy Collins’ Five Spot poem that have obvious applications to legal discovery, such as “There’s always a lesson to be learnedno matter which way it goes, for you or against, what you want to hear or what you don’t.” We are all trained to follow the facts, the trails, wherever they may lead, pro or con.

I do not say either pro or con “my case” because it is not. It is my client’s case. Clients pay lawyers for their knowledge, skill and independent advice. Although lawyers like to hear evidence that supports their client’s positions and recollections, after all it makes their job easier, they also want to hear evidence that goes against their client. They want to hear all sides of a story and understand what it means. They look at everything to craft a reasonable story for judge and jury.

Almost all cases have good and bad evidence on both sides. There is usually some merit to each side’s positions. Experienced lawyers look for the truth and present it in the best light favorable for their client. The Rules of Procedure and duties to the court and client require this too.

Bottom line for all e-discovery professionals is that you learn the lessons taught by the parties notes and documents, all of the lessons, good and bad.

The poem calls this a “… joyous impossible lesson in how to do it all at once, pleasing and displeasing yourself with harmony here and discord there.” All lawyers know this place, this joyless lesson of discovering the holes in your client’s case. As far as the “doing it all at once ” phrase, this too is very familiar to any e-discovery professional. If it is done right, at the beginning of a case, the activity is fast and furious. Kind of like a Roland Kirk solo, but without Roland’s exuberance.

Everybody knows that the many tasks of e-discovery must be done quickly and pretty much all at once at the beginning of a case: preservation notices, witness interviews, ESI collection, processing and review. The list goes on and on. Yet, in spite of this knowledge, most everyone still treats e-discovery as if they had bags of time to do it. Which brings me to another Billy Collins poem that I like:

BAGS OF TIME

When the keeper of the inn
where we stayed in the Outer Hebrides
said we had bags of time to catch the ferry,
which we would reach by traversing the causeway
between this island and the one to the north,

I started wondering what a bag of time
might look like and how much one could hold.
Apparently, more than enough time for me
to wonder about such things,
I heard someone shouting from the back of my head.

Then the ferry arrived, silent across the water,
at the Lochmaddy Ferry Terminal,
and I was still thinking about the bags of time
as I inched the car clanging onto the slipway
then down into the hold for the vehicles.

Yet it wasn’t until I stood at the railing
of the upper deck with a view of the harbor
that I decided that a bag of time
should be the same color as the pale blue
hull of the lone sailboat anchored there.

And then we were in motion, drawing back
from the pier and turning toward the sea
as ferries had done for many bags of time,
I gathered from talking to an old deckhand,
who was decked out in a neon yellow safety vest,

and usually on schedule, he added,
unless the weather has something to say about it.

Conclusion

Take time out to relax and let yourself ponder the works of a poet. We have bags of time in our life for that. Poetry is liable to make you a better person and a better lawyer.

I leave you with two videos of poetry readings by Billy Collins, the first at the Obama White House. He is by far my favorite contemporary poet. Look for some of his poems on dogs and cats. They are especially good for any pet lovers like me.

One More Billy Collins video.

 


TAR Course Expands Again: Standardized Best Practice for Technology Assisted Review

February 11, 2018

The TAR Course has a new class, the Seventeenth Class: Another “Player’s View” of the Workflow. Several other parts of the Course have been updated and edited. It now has Eighteen Classes (listed at end). The TAR Course is free and follows the Open Source tradition. We freely disclose the method for electronic document review that uses the latest technology tools for search and quality controls. These technologies and methods empower attorneys to find the evidence needed for all text-based investigations. The TAR Course shares the state of the art for using AI to enhance electronic document review.

The key is to know how to use the document review search tools that are now available to find the targeted information. We have been working on various methods of use since our case before Judge Andrew Peck in Da Silva Moore in 2012. After we helped get the first judicial approval of predictive coding in Da Silva, we began a series of several hundred document reviews, both in legal practice and scientific experiments. We have now refined our method many times to attain optimal efficiency and effectiveness. We call our latest method Hybrid Multimodal IST Predictive Coding 4.0.

The Hybrid Multimodal method taught by the TARcourse.com combines law and technology. Successful completion of the TAR course requires knowledge of both fields. In the technology field active machine learning is the most important technology to understand, especially the intricacies of training selection, such as Intelligently Spaced Training (“IST”). In the legal field the proportionality doctrine is key to the  pragmatic application of the method taught at TAR Course. We give-away the information on the methods, we open-source it through this publication.

All we can transmit by online teaching is information, and a small bit of knowledge. Knowing the Information in the TAR Course is a necessary prerequisite for real knowledge of Hybrid Multimodal IST Predictive Coding 4.0. Knowledge, as opposed to Information, is taught the same way as advanced trial practice, by second chairing a number of trials. This kind of instruction is the one with real value, the one that completes a doc review project at the same time it completes training. We charge for document review and throw in the training. Information on the latest methods of document review is inherently free, but Knowledge of how to use these methods is a pay to learn process.

The Open Sourced Predictive Coding 4.0 method is applied for particular applications and search projects. There are always some customization and modifications to the default standards to meet the project requirements. All variations are documented and can be fully explained and justified. This is a process where the clients learn by doing and following along with Losey’s work.

What he has learned through a lifetime of teaching and studying Law and Technology is that real Knowledge can never be gained by reading or listening to presentations. Knowledge can only be gained by working with other people in real-time (or near-time), in this case, to carry out multiple electronic document reviews. The transmission of knowledge comes from the Q&A ESI Communications process. It comes from doing. When we lead a project, we help students to go from mere Information about the methods to real Knowledge of how it works. For instance, we do not just make the Stop decision, we also explain the decision. We share our work-product.

Knowledge comes from observing the application of the legal search methods in a variety of different review projects. Eventually some Wisdom may arise, especially as you recover from errors. For background on this triad, see Examining the 12 Predictions Made in 2015 in “Information → Knowledge → Wisdom” (2017). Once Wisdom arises some of the sayings in the TAR Course may start to make sense, such as our favorite “Relevant Is Irrelevant.” Until this koan is understood, the legal doctrine of Proportionality can be an overly complex weave.

The TAR Course is now composed of eighteen classes:

  1. First Class: Background and History of Predictive Coding
  2. Second Class: Introduction to the Course
  3. Third Class:  TREC Total Recall Track, 2015 and 2016
  4. Fourth Class: Introduction to the Nine Insights from TREC Research Concerning the Use of Predictive Coding in Legal Document Review
  5. Fifth Class: 1st of the Nine Insights – Active Machine Learning
  6. Sixth Class: 2nd Insight – Balanced Hybrid and Intelligently Spaced Training (IST)
  7. Seventh Class: 3rd and 4th Insights – Concept and Similarity Searches
  8. Eighth Class: 5th and 6th Insights – Keyword and Linear Review
  9. Ninth Class: 7th, 8th and 9th Insights – SME, Method, Software; the Three Pillars of Quality Control
  10. Tenth Class: Introduction to the Eight-Step Work Flow
  11. Eleventh Class: Step One – ESI Communications
  12. Twelfth Class: Step Two – Multimodal ECA
  13. Thirteenth Class: Step Three – Random Prevalence
  14. Fourteenth Class: Steps Four, Five and Six – Iterative Machine Training
  15. Fifteenth Class: Step Seven – ZEN Quality Assurance Tests (Zero Error Numerics)
  16. Sixteenth Class: Step Eight – Phased Production
  17. Seventeenth Class: Another “Player’s View” of the Workflow (class added 2018)
  18. Eighteenth Class: Conclusion

With a lot of hard work you can complete this online training program in a long weekend, but most people take a few weeks. After that, this course can serve as a solid reference to consult during complex document review projects. It can also serve as a launchpad for real Knowledge and eventually some Wisdom into electronic document review. TARcourse.com is designed to provide you with the Information needed to start this path to AI enhanced evidence detection and production.

 


WHY I LOVE PREDICTIVE CODING: Making Document Review Fun Again with Mr. EDR and Predictive Coding 4.0

December 3, 2017

Many lawyers and technologists like predictive coding and recommend it to their colleagues. They have good reasons. It has worked for them. It has allowed them to do e-discovery reviews in an effective, cost efficient manner, especially the big projects. That is true for me too, but that is not why I love predictive coding. My feelings come from the excitement, fun, and amazement that often arise from seeing it in action, first hand. I love watching the predictive coding features in my software find documents that I could never have found on my own. I love the way the AI in the software helps me to do the impossible. I really love how it makes me far smarter and skilled than I really am.

I have been getting those kinds of positive feelings consistently by using the latest Predictive Coding 4.0 methodology (shown right) and KrolLDiscovery’s latest eDiscovery.com Review software (“EDR”). So too have my e-Discovery Team members who helped me to participate in TREC 2015 and 2016 (the great science experiment for the latest text search techniques sponsored by the National Institute of Standards and Technology). During our grueling forty-five days of experiments in 2015, and again for sixty days in 2016, we came to admire the intelligence of the new EDR software so much that we decided to personalize the AI as a robot. We named him Mr. EDR out of respect. He even has his own website now, MrEDR.com, where he explains how he helped my e-Discovery Team in the 2015 and 2015 TREC Total Recall Track experiments.

Bottom line for us from this research was to prove and improve our methods. Our latest version 4.0 of Predictive Coding, Hybrid Multimodal IST Method is the result. We have even open-sourced this method, well most of it, and teach it in a free seventeen-class online program: TARcourse.com. Aside from testing and improving our methods, another, perhaps even more important result of TREC for us was our rediscovery that with good teamwork, and good software like Mr. EDR at your side, document review need never be boring again. The documents themselves may well be boring as hell, that’s another matter, but the search for them need not be.

How and Why Predictive Coding is Fun

Steps Four, Five and Six of the standard eight-step workflow for Predictive Coding 4.0 is where we work with the active machine-learning features of Mr. EDR. These are its predictive coding features, a type of artificial intelligence. We train the computer on our conception of relevance by showing it relevant and irrelevant documents that we have found. The software is designed to then go out and find all other relevant documents in the total dataset. One of the skills we learn is when we have taught enough and can stop the training and complete the document review. At TREC we call that the Stop decision. It is important to keep down the costs of document review.

We use a multimodal approach to find training documents, meaning we use all of the other search features of Mr. EDR to find relevant ESI, such as keyword searches, similarity and concept. We iterate the training by sample documents, both relevant and irrelevant, until the computer starts to understand the scope of relevance we have in mind. It is a training exercise to make our AI smart, to get it to understand the basic ideas of relevance for that case. It usually takes multiple rounds of training for Mr. EDR to understand what we have in mind. But he is a fast learner, and by using the latest hybrid multimodal IST (“intelligently spaced learning“) techniques, we can usually complete his training in a few days. At TREC, where we were moving fast after hours with the Ã-Team, we completed some of the training experiments in just a few hours.

After a while Mr. EDR starts to “get it,” he starts to really understand what we are after, what we think is relevant in the case. That is when a happy shock and awe type moment can happen. That is when Mr. EDR’s intelligence and search abilities start to exceed our own. Yes. It happens. The pupil then starts to evolve beyond his teachers. The smart algorithms start to see patterns and find evidence invisible to us. At that point we sometimes even let him train himself by automatically accepting his top-ranked predicted relevant documents without even looking at them. Our main role then is to determine a good range for the automatic acceptance and do some spot-checking. We are, in effect, allowing Mr. EDR to take over the review. Oh what a feeling to then watch what happens, to see him keep finding new relevant documents and keep getting smarter and smarter by his own self-programming. That is the special AI-high that makes it so much fun to work with Predictive Coding 4.0 and Mr. EDR.

It does not happen in every project, but with the new Predictive Coding 4.0 methods and the latest Mr. EDR, we are seeing this kind of transformation happen more and more often. It is a tipping point in the review when we see Mr. EDR go beyond us. He starts to unearth relevant documents that my team would never even have thought to look for. The relevant documents he finds are sometimes completely dissimilar to any others we found before. They do not have the same keywords, or even the same known concepts. Still, Mr. EDR sees patterns in these documents that we do not. He can find the hidden gems of relevance, even outliers and black swans, if they exist. When he starts to train himself, that is the point in the review when we think of Mr. EDR as going into superhero mode. At least, that is the way my young e-Discovery Team members likes to talk about him.

By the end of many projects the algorithmic functions of Mr. EDR have attained a higher intelligence and skill level than our own (at least on the task of finding the relevant evidence in the document collection). He is always lighting fast and inexhaustible, even untrained, but by the end of his training, he becomes a search genius. Watching Mr. EDR in that kind of superhero mode is what makes Predictive Coding 4.0 a pleasure.

The Empowerment of AI Augmented Search

It is hard to describe the combination of pride and excitement you feel when Mr. EDR, your student, takes your training and then goes beyond you. More than that, the super-AI you created then empowers you to do things that would have been impossible before, absurd even. That feels pretty good too. You may not be Iron Man, or look like Robert Downey, but you will be capable of remarkable feats of legal search strength.

For instance, using Mr. EDR as our Iron Man-like suits, my e-discovery Ã-Team of three attorneys was able to do thirty different review projects and classify 17,014,085 documents in 45 days. See 2015 TREC experiment summary at Mr. EDR. We did these projects mostly at nights, and on weekends, while holding down our regular jobs. What makes this crazy impossible, is that we were able to accomplish this by only personally reviewing 32,916 documents. That is less than 0.2% of the total collection. That means we relied on predictive coding to do 99.8% of our review work. Incredible, but true.

Using traditional linear review methods it would have taken us 45 years to review that many documents! Instead, we did it in 45 days. Plus our recall and precision rates were insanely good. We even scored 100% precision and 100% recall in one TREC project in 2015 and two more in 2016. You read that right. Perfection. Many of our other projects attained scores in the high and mid nineties. We are not saying you will get results like that. Every project is different, and some are much more difficult than others. But we are saying that this kind of AI-enhanced review is not only fast and efficient, it is effective.

Yes, it’s pretty cool when your little AI creation does all the work for you and makes you look good. Still, no robot could do this without your training and supervision. We are a team, which is why we call it hybrid multimodal, man and machine.

Having Fun with Scientific Research at TREC 2015 and 2016

During the 2015 TREC Total Recall Track experiments my team would sometimes get totally lost on a few of the really hard Topics. We were not given legal issues to search, as usual. They were arcane technical hacker issues, political issues, or local news stories. Not only were we in new fields, the scope of relevance of the thirty Topics was never really explained. (We were given one to three word explanations in 2015, in 2016 we got a whole sentence!) We had to figure out intended relevance during the project based on feedback from the automated TREC document adjudication system. We would have some limited understanding of relevance based on our suppositions of the initial keyword hints, and so we could begin to train Mr. EDR with that. But, in several Topics, we never had any real understanding of exactly what TREC thought was relevant.

This was a very frustrating situation at first, but, and here is the cool thing, even though we did not know, Mr. EDR knew. That’s right. He saw the TREC patterns of relevance hidden to us mere mortals. In many of the thirty Topics we would just sit back and let him do all of the driving, like a Google car. We would often just cheer him on (and each other) as the TREC systems kept saying Mr. EDR was right, the documents he selected were relevant. The truth is, during much of the 45 days of TREC we were like kids in a candy store having a great time. That is when we decided to give Mr. EDR a cape and superhero status. He never let us down. It is a great feeling to create an AI with greater intelligence than your own and then see it augment and improve your legal work. It is truly a hybrid human-machine partnership at its best.

I hope you get the opportunity to experience this for yourself someday. The TREC experiments in 2015 and 2016 on recall in predictive coding are over, but the search for truth and justice goes on in lawsuits across the country. Try it on your next document review project.

Do What You Love and Love What You Do

Mr. EDR, and other good predictive coding software like it, can augment our own abilities and make us incredibly productive. This is why I love predictive coding and would not trade it for any other legal activity I have ever done (although I have had similar highs from oral arguments that went great, or the rush that comes from winning a big case).

The excitement of predictive coding comes through clearly when Mr. EDR is fully trained and able to carry on without you. It is a kind of Kurzweilian mini-singularity event. It usually happens near the end of the project, but can happen earlier when your computer catches on to what you want and starts to find the hidden gems you missed. I suggest you give Predictive Coding 4.0 and Mr. EDR a try. To make it easier I open-sourced our latest method and created an online course. TARcourse.com. It will teach anyone our method, if they have the right software. Learn the method, get the software and then you too can have fun with evidence search. You too can love what you do. Document review need never be boring again.

Caution

One note of caution: most e-discovery vendors, including the largest, do not have active machine learning features built into their document review software. Even the few that have active machine learning do not necessarily follow the Hybrid Multimodal IST Predictive Coding 4.0 approach that we used to attain these results. They instead rely entirely on machine-selected documents for training, or even worse, rely entirely on random selected documents to train the software, or have elaborate unnecessary secret control sets.

The algorithms used by some vendors who say they have “predictive coding” or “artificial intelligence” are not very good. Scientists tell me that some are only dressed-up concept search or unsupervised document clustering. Only bona fide active machine learning algorithms create the kind of AI experience that I am talking about. Software for document review that does not have any active machine learning features may be cheap, and may be popular, but they lack the power that I love. Without active machine learning, which is fundamentally different from just “analytics,” it is not possible to boost your intelligence with AI. So beware of software that just says it has advanced analytics. Ask if it has “active machine learning“?

It is impossible to do the things described in this essay unless the software you are using has active machine learning features.  This is clearly the way of the future. It is what makes document review enjoyable and why I love to do big projects. It turns scary to fun.

So, if you tried “predictive coding” or “advanced analytics” before, and it did not work for you, it could well be the software’s fault, not yours. Or it could be the poor method you were following. The method that we developed in Da Silva Moore, where my firm represented the defense, was a version 1.0 method. Da Silva Moore v. Publicis Groupe, 287 F.R.D. 182, 183 (S.D.N.Y. 2012). We have come a long way since then. We have eliminated unnecessary random control sets and gone to continuous training, instead of train then review. This is spelled out in the TARcourse.com that teaches our latest version 4.0 techniques.

The new 4.0 methods are not hard to follow. The TARcourse.com puts our methods online and even teaches the theory and practice. And the 4.0 methods certainly will work. We have proven that at TREC, but only if you have good software. With just a little training, and some help at first from consultants (most vendors with bona fide active machine learning features will have good ones to help), you can have the kind of success and excitement that I am talking about.

Do not give up if it does not work for you the first time, especially in a complex project. Try another vendor instead, one that may have better software and better consultants. Also, be sure that your consultants are Predictive Coding 4.0 experts, and that you follow their advice. Finally, remember that the cheapest software is almost never the best, and, in the long run will cost you a small fortune in wasted time and frustration.

Conclusion

Love what you do. It is a great feeling and sure fire way to job satisfaction and success. With these new predictive coding technologies it is easier than ever to love e-discovery. Try them out. Treat yourself to the AI high that comes from using smart machine learning software and fast computers. There is nothing else like it. If you switch to the 4.0 methods and software, you too can know that thrill. You can watch an advanced intelligence, which you helped create, exceed your own abilities, exceed anyone’s abilities. You can sit back and watch Mr. EDR complete your search for you. You can watch him do so in record time and with record results. It is amazing to see good software find documents that you know you would never have found on your own.

Predictive coding AI in superhero mode can be exciting to watch. Why deprive yourself of that? Who says document review has to be slow and boring? Start making the practice of law fun again.

Here is the PDF version of this article, which you may download and distribute, so long as you do not revise it or charge for it.

 

 


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