Second Class: Introduction
Welcome to the second class in this course. Here we introduce the basic concepts behind Predictive Coding 4.0, listed below. Then we review the basic e-discovery skills and knowledge that all students are expected to know before continuing this study. They are:
- Active Machine Learning (aka Predictive Coding)
- Concept & Similarity Searches (aka Passive Learning)
- Keyword Search (tested, Boolean, parametric)
- Focused Linear Search (key dates & people)
- GIGO & QC (Garbage In, Garbage Out) (Quality Control)
- Balanced Hybrid (man-machine balance with IST)
- SME (Subject Matter Expert, typically trial counsel)
- Method (for electronic document review)
- Software (for electronic document review)
- Talk (step 1 – relevance dialogues)
- ECA (step 2 – early case assessment using all methods)
- Random (step 3 – prevalence range estimate, not control sets)
- Select (step 4 – choose documents for training machine)
- AI Rank (step 5 – machine ranks documents according to probabilities)
- Review (step 6 – attorneys review and code documents)
- Zen QC (step 7 – Zero Error Numerics Quality Control procedures)
- Produce (step 8 – production of relevant, non-privileged documents)
The first nine concepts listed above are insights. They are shown in the chart below.
The last eight points covered in this course are the workflow steps shown in the circular chart below that describes our Hybrid Multimodal IST method for document review, aka – Predictive Coding 4.0.
The next video will “tell again” what the course will cover. The class will then conclude by reviewing the nine basic e-discovery skills. Knowledge of these skills is assumed in the TAR Course, which is an advanced program. You do not have to be a lawyer to benefit from the TAR Course, but you do have to understand all of these basics to fully grasp many of the subtle points taught here.
Prerequisites for the TAR Course and the Ethical Duty of Competence Under Model Rule 1.1
The advanced search methods taught in this course build upon and assume basic knowledge of e-discovery legal services. In other words, this course is designed for students who are already competent in the basics of this field. Many of the skills that all attorneys should know to meet their duty of competence under Model Ethics Rule 1.1 are listed in a California Ethics Opinion. The State Bar of California Standing Committee on Professional Responsibility and Conduct Formal Opinion No. 2015-193 (final version August 2016). These basic skills provide an important background for the more specialized search skills taught in the TAR Course. For that reason we address all nine general e-discovery skills needed for basic competence before we go further in this specialized training. Experts can safely skip the remainder of this class.
Just a few years ago the skills and knowledge required to perform the services described in the California Opinion 2015-193 were considered arcane. They were known only by e-discovery specialists. The California Bar has taken a bold leap forward to make this kind of knowledge required for all attorneys who litigate in California. The California Bar has thus raised the bar of competence for everyone by making this an ethical imperative. Note, that as footnote seven to the Opinion makes clear, this is not intended to be an exhaustive list. For instance, attorneys must also know how to properly obtain an opposing party’s ESI. That should really be included as the tenth step.
California Formal Opinion on Ethics No. 2015-193 (final version August 2016), at pages 3-4:
Attorneys handling e-discovery should be able to perform (either by themselves or in association with competent co-counsel or expert consultants) the following:
1. Initially assess e-discovery needs and issues, if any;
2. Implement/cause to implement appropriate ESI preservation procedures;
3. Analyze and understand a client’s ESI systems and storage;
4. Advise the client on available options for collection and preservation of ESI;
5. Identify custodians of potentially relevant ESI;
6. Engage in competent and meaningful meet and confer with opposing counsel concerning an e-discovery plan;
7. Perform data searches;
8. Collect responsive ESI in a manner that preserves the integrity of that ESI; and
9. Produce responsive non-privileged ESI in a recognized and appropriate manner. FN7
FN 7 – This opinion focuses on an attorney’s ethical obligations relating to his own client’s ESI and, therefore, this list focuses on those issues. This opinion does not address the scope of an attorney’s duty of competence relating to obtaining an opposing party’s ESI.
If this is all new to you, and the nine-skills are still somewhat unclear, then you might want to refresh or improve your general e-discovery skills. To do so we suggest you take the free e-Discovery Team training course. We also suggest that you study our related instructional website, EDBP.com, where we have a collection of best practices for legal services summarized by the chart below.
These include the minimum skills required by California and much more. The proper placement of the California Nine in the EDBP would be as follows.
By the way, CAR is the same thing as TAR. It stands for Computer Assisted Review. The California task seven of search involves both the Culling and C.A.R. step in the EDBP. California’s ninth task bundles protection of privilege with correct production. They are really two different tasks and it diminishes both by combining them like California has done. The EDBP splits this into two steps.
Or pause to do this suggested “homework” assignment for further study and analysis.
SUPPLEMENTAL READING: If you have not already done so, go to the Team’s TAR page and look around. Also read in full the related web created by the Team: Legal Search Science. Also read Losey’s My Basic Plan for Document Reviews: The “Bottom Line Driven” Approach article. It was written in October 2013 and so describes old, dated version 2.0 methods of multimodal hybrid document review. But it still contains important background discussions, especially to understand the economics and proportionality considerations in predictive coding. Next search and find the law review article that Losey wrote that also embodies these old methods. It also provides important background reading and has good citations and analysis that you will not find elsewhere. Plus, as a law review article, it is good to cite for the main points that are still valid. Finally, study carefully the entire text of The State Bar of California Standing Committee on Professional Responsibility and Conduct Formal Opinion No. 2015-193.
EXERCISES: Here are several exercises for this first introductory class:
- Consider why the profession has moved so slowly to adopt predictive coding in spite of the benefits. It was first approved by Judge Peck in my Da Silva Moore case back in February 2012, and yet is still seldom used.
- Try to consider what arguments you would use with opposing counsel to persuade them that they should use predictive coding to search for the documents you have requested?
- What arguments would you use to persuade a judge to approve of your use, assuming the requesting party foolishly opposed it?
- What arguments would you use to persuade a judge to force a responding party to use predictive coding?
- If you do not already know the case, find the opinion by Judge Peck that addresses this last questions. Speculate on different conditions that might cause Judge Peck to reach a different conclusion.
- Make up your own list like California has done. Make one list that is like California that does not try to be inclusive, and make up another one that tries to capture the many tasks (under 30 please). Then try and see how they would all fit into the EDBP structure.
Students are invited to leave a public comment below. Insights that might help other students are especially welcome. Let’s collaborate!
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