Predictive Coding Technologies for the Modern Lawyer

• Pages: 29-29
• Date: 01 July 2023
• Author: Rachel A. Harris
• Subject Matter: Civil Law

Published in Litigation News Volume 48, Number 4, Summer 2 023. © 2023 by the Amer ican Bar Association . Reproduced with pe rmission. All rights re served. This info rmation or any porti on thereof may not be c opied or disseminated in an y

form or by any means or sto red in an electronic da tabase or retrieval sy stem without the ex press writt en consent of the Amer ican Bar Associatio n.

BOOK REVIEW

Gone are the days of purely manual document

review. Today, lawyers are accustomed to prac-

ticing within a digital world built on troves of

electronically stored information (ESI). As our

modern world becomes even more reliant on

the Internet of Things, discovery of ESI can result in wading

through terabytes of data. Faced with this and the Federal

Rules of Civil Procedure’s mandate “to secure the just, speedy,

and inexpensive determination of every action and proceed-

ing,” there has been an increasing acceptance of advanced

e-discovery techniques by courts and practitioners.

Perspectives on Predictive Coding and Other Advanced

Search Methods for the Legal Practitioner, edited by Jason R.

Baron, Michael D. Berman, and Ralph C. Losey, is a denitive

resource for lawyers looking to understand where e-discovery

stands today and where the eld may be headed in the near

future. For those specialists who operate within the e-discovery

industry, the book details the latest technology and how courts

are responding. As one of the book’s editors noted, “[t]oday,

every lawyer conducting ‘discovery’ in civil litigation needs

to confront the fact that—no matter how large or small the

case may be—it is insufcient to simply dene the search task

as being limited to nding relevant documents in traditional

paper les. The legal profession lives and breathes in a world

of [ESI]. . . .”

Each of the book’s three editors graduated from law school

in 1980, so they have witnessed rsthand how discovery prac-

tice has transformed from searching through paper les to

utilizing automated technology tools and continuous machine

learning to expedite the review process. They have spent over

a decade engaged in researching, writing, and teaching about

how lawyers can search electronic evidence using smarter

methods than manual and keyword searching.

The book is a substantial 20 chapters by various authors,

divided into four parts. In the rst part, the book provides

preliminary observations about the limitations of traditional

e-discovery search techniques, such as keyword searching and

deduplication. The authors then explore the emerging accep-

tance of technology-assisted review (TAR) by the courts, high-

lighting key cases along the way.

In the second part, the book explains the differences among

various automated tools and methods that are grouped within

the TAR label, the differences between passive and active

machine-learning techniques, and the differences between

simple versus continuous machine learning. A framework is

also provided for developing customized predictive coding

workows. Notably, various perspectives are presented, includ-

ing from the federal and state courts, the plaintiffs’ and defen-

Predictive Coding Technologies for

the Modern Lawyer

Perspectives on Predictive Coding is available at http://bit.ly/LN484-perspectives.

dants’ bar, and small and

large cases.

In the third part,

leading experts in the

burgeoning eld of infor-

mation retrieval explain

the metrics that lawyers

need to understand to

be able to measure and

evaluate the effectiveness

of predictive coding and

other advanced search

technologies. The authors

explore quantitative, sta-

tistical tools that function

to ensure and demonstrate

a high-quality and cost-

effective review, while also

presenting practitioner

guides for measuring cost-for-completion tradeoffs while using

advanced search technologies. Along the way, the authors also

explore existing e-discovery standards, why there are so many

competing standards efforts when it comes to predictive cod-

ing, and what kind of standards operating outside the federal

rules could be applied to e-discovery practice.

In the fourth and nal part, the book explores how

advanced search methods are being integrated into aspects of

legal practice outside of litigation. For example, the authors

explore the use of predictive analytics in mergers, acquisi-

tions, and divestitures and its use in overall information gov-

ernance. In the nal chapter, author Kathryn Hume explores

how the near future may involve even more advanced search

methods springing from the eld of deep learning and neural

networks,”a type of machine learning using multiple comput-

ing layers designed to mimic the brain.

Comment 8 to Model Rule of Professional Conduct 1.1—

which relates to the “competence” of counsel—states that “a

lawyer should keep abreast of changes in the law and its prac-

tice, including the benets and risks associated with relevant

technology[.]” Thus, the litigator’s obligation to keep up with

developments in e-discovery and information search technol-

ogy is not optional. Perspectives on Predictive Coding and

Other Advanced Search Methods for the Legal Practitioner is a

new resource for cutting-edge electronic discovery technology

that every lawyer needs.

By Rachel A. Harr is, Litigation News Contributing E ditor

SUMMER 2 023 • VOL. 48 NO. 4

29 | ABA LITIGATION SECTIO N