Microsoft Word - Cover Pg. - ARTIFICIAL INTELLIGENCE AND THE
PRACTICE OF LAWCAN A COMPUTER THINK LIKE A LAWYER?
Presented by: DAVID E. CHAMBERLAIN
TIMOTHY B. POTEET Chamberlain McHaney
301 Congress, 21st Floor Austin, Texas 78701
State Bar of Texas 8TH ANNUAL
BUSINESS DISPUTES September 22-23, 2016
Houston
Austin, Texas 78701 512/474-9124
David E. Chamberlain has been recognized as The
Outstanding Defense Bar Leader in the nation by DRI, the largest
association of defense trial lawyers in the country (Fred Sievert
Award, 2006). He currently serves on the Board of Directors of the
State Bar of Texas and Chairs the Board of Trustees of the State
Bar of Texas Insurance Trust. In 2011-12 he served as President of
the Austin Bar Association, the year it was named the Outstanding
Local Bar Association, Div. IV, by the State Bar of Texas. He
formerly served on DRI’s National Board of Directors. In 2008, he
was named The Outstanding Board Director of the Austin Bar
Association. He has served as President of the Texas Association of
Defense Counsel (2004-2005) and in 2009 received the association’s
Founder’s Award for outstanding leadership and service to the
profession. He is currently President-elect of Tex-ABOTA and also
serves as an officer of the Austin Chapter. He chairs the Texas
Chapters’ Legislative Committee. He is named in the peer- selected
BEST LAWYERS IN AMERICA and has been named a Texas Super Lawyer for
eight straight years in Texas Monthly Magazine (2005-2014) (limited
to 5% of Texas attorneys) and has also been named National Super
Lawyer, Corporate Counsel Edition for the past four years
(2008-2014). He is Board Certified in Personal Injury Trial Law by
the Texas Board of Legal Specialization (less than 3% of Texas
attorneys are board certified in this practice area). He is the
senior partner in the Austin civil trial firm of
Chamberlain♦McHaney and has had the highest peer
review rating (A.V. – Pre-eminent) issued by Martindale- Hubbell
for over 25 years. He serves and has served as the Course Director
of the State Bar of Texas Advanced Civil Trial Law Course (2014),
State Bar of Texas Advanced Personal Injury Law Course (2006) and
the State Bar of Texas Business Disputes Institute (2013).
Activities & Honors:
Director, Board of Directors of the State Bar of Texas
(2013-2016);
President, Austin Bar Association (elected 2011-2012) (Named the
Outstanding Local Bar Association, 2011- 12, by the State Bar of
Texas; Received the Luminary Award 2011-2012 for Excellence in
Communication from the National Association of Bar
Executives;
President-elect, Texas Chapters of American Board of Trial
Advocates (Tex-ABOTA) and chair of its Legislative Committee;
(2012–Present);
Chair, Board of Trustees, State Bar of Texas Insurance Trust
(2014-Present);
National Director, Board of Directors, DRI (the largest association
of defense trial attorneys in North America and Europe)
(2009-2012);
Chair, Austin Bar Foundation (2012-2013)(Charitable arm of the
Austin Bar)
President, Texas Association of Defense Counsel, 2004-2005
(President-Elect, 2003-2004; Executive Vice-President, 2002-2003;
Secretary-Treasurer 2000- 2001; Founder’s Award, 2009; President’s
Award, 1991 and 1999); Program Chair, 2011 Annual Meeting; Program
Chair, 2013 Summer Meeting;
Secretary, American Board of Trial Advocates; Austin Chapter
(2011-Present);
DRI (named Outstanding Defense Bar Leader in the nation in 2006;
State Leadership Award, 2009; Exceptional Performance Award, 2005;
Chair, Public Service Committee, 2010-11; National Membership
Committee, 2007 to 2009; Texas State Representative, 2006-2009;
Regional Marketing Chair (2006-2009);
Fellow, Foundation of the American Board of Trial Advocates
Member, Supreme Court of Texas Expedited Actions Task Force
(2011-2012);
Chair, TEX-ABOTA/TTLA/TADC HB 274 Working Group on New Civil
Procedure Rules (2011);
Chair, Legislative Committee, Austin Bar Association (2008 to
present);
President, Austin Young Lawyers Association (1987- 1988);
Board of Directors, Texas Civil Justice League, (2004- 2011);
State Bar of Texas (Course Director, Advanced Civil Trial Law
Course, 2014; Course Director, Business Disputes Institute, 2013;
Course Director, Advanced Personal Injury Law Course, 2007;
Planning Committee; Advanced Personal Injury Law Course, 2012,
2011, 2010, 2009, 2008 and 2006; Planning Committee, Texas Business
Torts, 2012, 2011, 2009; Planning Committee, Damages in Civil
Litigation, 2013; Planning Committee, Advanced Insurance Law
Course, 2008; Planning Committee, Advanced Civil Trial Law Course,
2005; Member, Court Administration Task Force, 2007-2008);
Chairman, State Bar Jury Project, 2005-2006; Court Rules Committee,
1997-2000; Sunset Committee, 2002- 2003);
Board of Directors, Austin Bar Association (1987- 1988);
Association of Defense Trial Attorneys; Federation of Defense and
Corporate Counsel; Bar Association of the Fifth Circuit; Sustaining
Life Fellow, Texas Bar Foundation
(Nominating Chairman, 2000-2001) (Selection Committee, Dan R. Price
Award, 2009);
Member, College of the State Bar of Texas (2001- present)
American Bar Association
BOARD CERTIFICATION: Personal Injury Trial Law, Texas Board of
Legal Specialization (less than 10% of Texas attorneys are board
certified in any practice area and less than 3% are board certified
in personal injury trial law).
Admissions: State Bar of Texas; Fifth Circuit Court of Appeals; All
U.S.
District Courts; Northern, Eastern, Southern and Western
Districts.
Author and Speaker: Recent topics and publications include:
Proposed New Disciplinary Rules of Professional Conduct (State Bar
Advanced Personal Injury Course, 2010; Texas Association of Defense
Counsel, 2010);
Texas Legislative Update (State Bar Advanced Personal Injury
Course, 2012, 2011, 2009, 2008, 2007, 2006; State Bar of
Texas-Litigation Section, 2013, 2012; State Bar of Texas-Damages in
Civil Litigation, 2013, 2012; State Bar of Texas-Advanced Civil
Trial Law Course,
2013, 2012; University of Texas-Page Keeton Civil Litigation
Conference 2012; State Bar of Texas- Business Torts, 2013, 2012,
2011; TEX-ABOTA, 2013, 2012, 2011; Texas Association of Defense
Counsel, 2012, 2011, 2010, 2009; and Austin Bar Association, 2013,
2012, 2011, 2010, 2009 and 2007, and State Bar College,
2005);
Article, A Level Playing Field with No Wind, Voir Dire, the Journal
of the American Board of Trial Advocates, January 2012
Ethical Considerations in Business Litigation (State Bar of Texas
Business Torts Law Course, 2009); (Texas Association of Defense
Counsel, 2010).
“Paid or Incurred” How it works at Trial (2009 Austin Bar
Association Bench-Bar Annual Conference);
Judicial Tort Reform (State Bar Advanced Personal Injury Course,
2008);
Feature Article, The American Jury: The Best Alternative Dispute
Resolution, For The Defense (DRI, The Magazine of Defense,
Insurance and Corporate Counsel, June 2008);
Attorney Ethics (State Bar Advanced Personal Injury Law Course,
2008);
Insurance Coverage Update (State Bar Advanced Insurance Law Course,
2007, 2008); (University of Houston, Advanced Insurance Law Course,
2008);
The State of Our Seventh Amendment, Presented to the State Bar of
Texas Annual Meeting (2007);
Insurance Issues in Construction Defect Litigation (San Antonio
2007);
Article, Texas Legislative Update, Texas Bar Journal, State Bar of
Texas, January, 2007;
Tort Trends (Texas Causes of Action, State Bar of Texas,
2006);
Texas Tort Reform (2003 & 2004); Trying Tough Cases in Tough
Venues (Texas
Association of Defense Counsel, 2004); Mold Litigation (2002);
Daubert Overview (State Bar, Advanced Civil Law
Trial Course, 2000); Texas Summary Judgments (Rutter Group, 1997);
Chapter, Government Liability (1998); Insurance Coverage of
Employment Claims (Austin Bar
Association, 1997); Editor in Chief -Texas Update (2002 to
present).
Education: University of Texas at Arlington (B.A., 1975)
St. Mary’s University of San Antonio (J.D., with honors,
1978)
Note and Comment Editor, St. Mary’s Law Journal, 1977-1978
Phi Delta Phi (Vice President, 1978; Outstanding Law Graduate,
1978)
Harlan Honor Society.
Supreme Court, 1978-1979.
Recognized, Best Lawyers in America, 2012 - 2014. Recognized as
Texas Super Lawyer for eight straight years (2005-2014) in
Texas
Monthly Magazine and National Super Lawyer-Corporate Edition for
four straight years (2008-2014).
AV-Rated (highest peer review rating) by Martindale Hubbell for
over 25 years and listed in Best’s Directory of Recommended
Attorneys and Martindale Hubbell’s Bar Registry of Preeminent
Lawyers.
2012 GO-TO Litigation LAW FIRM for the Top 500 Companies, American
Financial Group
301 Congress, 21st Floor Austin, Texas 78701
512/474-9124 512/474-8582 (fax)
Tim Poteet handles civil trials, arbitrations, and appeals in state
and federal courts. Specific practice concentrations include
insurance, construction, intellectual property, commercial
litigation, and general tort litigation. Mr. Poteet has substantial
experience in complex construction litigation and appellate
practice before Texas and Federal courts. Recognition:
AV Preeminent® Peer Review Rated, Martindale-Hubbell (Highest
Rating) Life Fellow, Texas Bar Foundation
Education:
Bachelor of Arts (Government) with High Honors 1981 University of
Texas at Austin
Doctor of Jurisprudence 1984 University of Texas at Austin
Admissions: Supreme Court of Texas, 1984 United States Fifth
Circuit Court of Appeals United States District Court, Southern,
Northern, Western & Eastern Districts of Texas
Professional Associations:
Chamberlain ♦ McHaney, Member Author and Speaker:
Mr. Poteet writes and speaks on construction, insurance, and
litigation topics, including the annual Chamberlain♦McHaney
Ultimate Claims Handling Seminar, offered as continuing education
for the insurance industry and held in Dallas each October. His
most recent publications include:
Insurance Law Update
Professional Memberships: Defense Research Institute, Construction
Section Texas Association of Defense Counsel, Appellate Amicus
Committee Litigation Section, State Bar of Texas Construction
Section, State Bar of Texas Insurance Section, State Bar of Texas
Appellate Section, State Bar of Texas Austin Bar Association
Selected Appellate Opinions:
Materials Evaluation and Technology Corp. v. Mid-Continent Cas.
Co., No. 12-40186 (5th Cir. 2012) (Fifth Circuit Court of Appeals
agrees with client and lower court that insured was not entitled to
assume to a “renewal” policy had the same terms as prior policy
when the renewal policy endorsement indicated change in terms.)
Mid-Continent Casualty Co. v. Global Enercom Mgmt., 323 S.W.3d 151
(Tex. 2010) (Texas Supreme Court agrees with client, reversed lower
courts and enforced “auto use” exclusion to reject coverage claim
under $1M CGL policy arising from triple fatality accident, but
found coverage under $100K commercial auto policy.) Ramirez v.
Fifth Club, Inc., 196 S.W.3d 788 (Tex. 2006) (Texas Supreme Court
agrees with client and reversed lower court judgments and overruled
prior precedent in holding Texas law does not recognize a “personal
character” exception to general rule of non-liability for acts of
an independent contractor.) Graper v. Mid-Continent Casualty Co.,
No. 13-20099 (5th Cir. 2014)(Circuit Court of Appeals affirms
summary judgment for client insurer that insured was not entitled
to select counsel at insurer’s expense to defend copyright
infringement case because coverage issues would not be determined
in liability suit and extra-contractual claims were properly
dismissed.) Petroleum Solutions, Inc. v Head Enterprises, No.
11-0425 (Tex. 2014) (Texas Supreme Court applies new rules for
spoliation and reverses judgment against client based on trial
court’s abuse of discretion in imposing improper sanctions that
resulted in improper judgment.)
Artificial Intelligence and the Practice of Law Or Can a Computer
Think Like a Lawyer? Chapter 25
i
TABLE OF CONTENTS ARTICLE – Artificial Intelligence and the
Practice of Law Or can a Computer Think Like a Lawyer? ......
1-4
1
Can a Computer Think Like a Lawyer?
Everyone knows that computers crash, but what about cars driven by
computers? Media outlets report that self-driving cars are just
around the corner. With Google behind the wheel, we can go for a
drive and take a nap at the same time. The Google cars are being
designed for use without steering wheels or brakes, so the computer
would be fully in charge. In this manner, the driver is useless
intelligence. Earlier this year the legal media headlined the
arrival of artificially intelligent programs that soon would
displace lawyers, or at least some of them. One large law firm
attracted attention for purchasing a program that would do the work
of fresh associates in a bankruptcy practice, handling preparation
of routine forms and schedules.1 While this seems little different
from using software to prepare your tax returns, some proponents
heralded the development as a harbinger of profound change in the
legal profession, predicting the imminent arrival of robot lawyers.
Artificial intelligence (“AI”) is a term that generally refers to
computers performing mental tasks traditionally performed by
humans. Computer programs are developed by software engineers, but
those that are “artificially intelligent” are represented to have
the capacity to process information, then create new programs
independently based on the information processed. This is also
called cognitive computing. But there are distinctions between
so-called “hard” and “soft” artificial intelligence. “Hard”
artificial intelligence involves computers that actually reason in
a way similar to humans. This is the kind of artificial
intelligence displayed in Stanley Kubrick’s forward-thinking motion
picture “2001: A Space Odyssey,” which of course raised the specter
of a human-like computer that develops mental illness and becomes
homicidal (“I’m sorry, Dave. I’m afraid I can’t do that.” – HAL
9000).2
Both this kind of AI and the specter of deviant behavior remain in
the domain of futurists at this time, as AI software that truly
reasons the way a human
1 “In a First a BigLaw Firm Announces it Will Use Artificial
Intelligence in its Bankruptcy Practice.”
http://www.abajournal.com. 2 HAL is short for “heuristic
algorithm.” 3 “How Artificial Intelligence is Transforming the
Legal Profession,” http://www.abajournal.com.
reasons does not appear to be commercially available, if it even
exists. On the other hand, “soft” artificial intelligence, which
enables computers to perform human tasks, but faster, is on the
horizon if it has not already arrived. However, the extent of its
functionality, as well as its market penetration, remains to be
seen.
At least some of these programs are based on technology developed
for the IBM computer named Watson that beat human contestants in a
televised game show in 2011.3 Reportedly, Watson was an advance
from prior systems because its design enabled it to understand
natural language, including denotative and connotative meanings of
words, and its “vocabulary” expanded with use.4 Unlike a prior
program that excelled at chess—a game of “complete information
based entirely on math with finite possibilities,” Watson displayed
the capacity to answer open-ended questions involving natural
language.5 Obviously, those capabilities can be useful in a legal
context. That has led some observers to wonder whether
technological innovation will be an event of creative destruction
that will destroy the legal profession, or at least its traditional
structure, as more tasks performed by associate attorneys are
delegated to computer software. Proponents of the technology
emphasize that clients are demanding better value in terms of more
service at less cost, a need that only the power of artificial
intelligence can meet. At least one proprietor has suggested that
the traditional pyramid model of law firms has or will soon become
diamond- shaped.6 In reality, many of us already are using or at
least have available to using “soft” artificial intelligence in
legal research. We are accustomed to performing word or phrase
searches either in common search engines or in proprietary legal
research databases. The latter also offer “enhanced” results,
netting additional materials that the familiar Boolean search
method purportedly would not provide. It is suggested that these
programs would “learn” as they are used, such that their
capabilities and presumably their value would increase over time,
and be able to recognize not just words but concepts.
4 legaltalknetwork.com/podcasts/law-technology-
now/2016/05/artificial-intelligence-will-influence-future- legal 5
Id. 6 How Artificial Intelligence is Transforming the Legal
Profession,” http://www.abajournal.com.
2
The primary value in these systems clearly is in raw computing
power. No one could rationally dispute that computer programs can
“review” and search large quantities of data faster than any person
or group of people could. This is the computational process of
discovering patterns in large data sets involving methods at the
intersection of artificial intelligence, machine learning,
statistics, and database systems.7 This process is commonly
referred to as data mining. The actual data mining task is the
automatic or semi-automatic analysis of large quantities of data to
extract previously unknown, interesting patterns such as groups of
data records (cluster analysis), unusual records (anomaly
detection), and dependencies (association rule mining).8 Many users
of email and social media recognize (and often resent) data mining,
but it appears that the same or similar programs are employed to
extract patterns or specific pieces of information from copious
data collections, including programs with legal applications. Less
certain is the extent to which the programs actually can recognize
concepts, or even read anomalies in the material. For example,
documents scanned and converted into portable document format (pdf)
materials with content made “readable” by optical character
recognition, may contain errors and anomalies that the software
cannot read. Moreover, concept-recognition itself involves the
frequency of the incidence of co-related terms, and in that sense
at least appears to remain word-based. Legal concepts typically are
expressed in words. Concepts also can be expressed as algorithms,
which increasingly influence our daily lives, but most attorneys do
not directly employ—and some do not even understand—algorithms. The
developing software uses algorithms to analyze unstructured data,
but the output still must appear as words, at least in the near
term. While some foresee developing software as causing “a paradigm
shift in how legal work is done,” others believe change will be
incremental, and the effect will be to enhance the profession’s
ability to serve its clients rather than to replace the
professionals altogether.9
7 Wikipedia.org/wiki/Data_mining.
8 Wikipedia.org/wiki/Machine_learning. 9 “How Artificial
Intelligence is Transforming the Legal Profession,”
http://www.abajournal.com. 10 See id. 11 See id.
It is true that incremental change is less dramatic than
revolutionary change. The American Bar Association has published
material stating that “AI is the next great hope that will
revolutionize the legal profession.”10 A heavily promoted concept
is that the machine “learns” as it goes. Like us, the more it
works, the more it learns, but unlike us, the machine uses data
analytics and predictive coding to analyze unstructured data. This
reportedly enables the machine to identify what is relevant, to
detect patterns, to find results, and even to predict outcomes.11
Some observers have commented on the marketing aspect of
“artificial intelligence.”12 At a 2016 Vanderbilt Law School
conference about artificial intelligence, one speaker, who holds a
PhD in computer science, estimated “we’re currently experiencing
the second or third wave of A.I. hype,” in which everyone uses the
term to describe their technology.13 Referring to “predictive
coding” as the “flavor of the day,” the speaker nevertheless stated
that “there have been real advances in machine learning” and that
algorithms can “reduce the number of documents that lawyers must
review” and “probably [do] reduce the cost of a project.”14
A target market for some of these services appears to be companies
subject to regulatory or law enforcement with respect to claims
that may result or be in litigation, to predict and prevent
occurrences and to investigate what conduct led to an occurrence
that may be the basis for a claim or a charge. Software offering
predictive analytics would reduce risk on the front end for
enterprises employing it, resulting in reduced litigation expenses
and limiting exposure to adverse legal outcomes.15 Similarly, such
software reportedly may enable law enforcement or regulatory
authorities to review massive amounts of content, recognize
concepts, identify patterns of conduct, and assemble data
consisting of concentrated information relevant to the issue, such
as, for example, trade secret theft, or insider trading, and to the
collate data for use in the prosecution or defense of charges, or
litigation.16 Besides legal research of case law, legislation, and
other common collected digitized databases of authorities, the more
modest initial primary function of
12 bol.bna.com/artificial-intelligence-marketing-buzzword-
or-reality/ 13 See id. 14 Id. 15 See id. 16 See id.
3
AI in legal services appears to involve work at lower levels of
legal sophistication, particularly work involving preparation of
forms, such as forms employed in simple bankruptcies. This is not
dissimilar to the form-based legal work offered by legal publishers
for decades, or, more recently, the services offered by other
companies like Legal Zoom, which are essentially do-it-yourself
online programs. As noted, these programs employ algorithms. An
algorithm may be considered as a step-by-step set of operations to
be performed, or a type of formula. Algorithms are increasingly
prevalent if not omnipresent in the daily lives of people in
countries with developed economies, being used in the military,
business, finance, manufacturing, science, communications, media,
transportation, medicine, entertainment, and virtually every other
facet of economic and social life.
Various tools of artificial intelligence are also being widely
deployed in homeland security, speech and text recognition, data
mining, and e-mail spam filtering.17 Applications are also being
developed for gesture recognition (understanding of sign language
by machines), individual voice recognition, global voice
recognition (from a variety of people in a noisy room), and facial
expression recognition for interpretation of emotion and non-verbal
cues.18 Other applications are robot navigation, obstacle
avoidance, and object recognition.19
Exceeding common human brain power is nothing new.
Calculators do that. And some researchers have commented that when
AI functions become common, they are no longer considered
intelligent, or artificially intelligent.20 Again, there is a leap
from common algorithms used in, for example, our cell phones, to
“hard” artificial intelligence, which involves the ability of the
algorithm to reason automatically, including propagating its own
algorithms.21 Put another way, such artificial intelligence is the
program’s ability to improve its performance with use, or
“experience.” Some refer to such artificial intelligence as
“machine learning.”22 Machine learning and data mining often employ
the same methods and overlap significantly.23 They can be
roughly
17 wikipedia.org/wiki/Applications_of_artificial_intelligence. 18
Id. 19 Id. 20 Id. 21 wikipedia.org/wiki/Automated_reasoning. 22
Wikipedia.org/wiki/Machine_learning.
distinguished as follows: machine learning focuses on prediction,
based on known properties learned from the training data, while
data mining focuses on the discovery of (previously) unknown
properties in the data.24 Machine learning has been characterized
as being a method of data analysis that automates analytical model
building.25 Using algorithms that iteratively learn from data,
machine learning reportedly allows computers to find hidden
insights without being explicitly programmed where to look.26 As
models are exposed to new data, they are able to independently
adapt.27 The purpose is for the model to learn from previous
computations to produce reliable, repeatable results.28 Widely
publicized examples of machine learning applications include the
“self-driving” car, recommendation offers from online retailers and
streaming media, “targeted” advertising, among many others.29 Of
course, whether these applications actually produce results that
are beneficial to the end-user is another matter, and the same is
true of legal programs that employ software of this type. Some may
wonder—how are we going to rely on AI lawyers when we can't rely on
spell check? But many do and more will come to rely on form-based
or online legal services when an algorithm can process data with
far greater speed and efficiency and much less expense than a
person could, even if a person were available to assist. Most
often, no one is, because there is little economic incentive.
Computer technology makes it possible, and economies of scale make
to feasible, to provide such services in relatively simple matters
that don’t require “legal reasoning.” This may apply, for example,
to simple divorces, minor dispute resolution, preparing simple
wills and small corporations, among many other legal needs—even
fixing traffic tickets. Notably, however, all such programs are
subject to the “GIGO” rule— garbage in equals garbage out. It will
remain necessary for a human monitor to verify the data being
scanned and for a human witness to lay the predicate for its
admissibility in a proceeding subject to traditional rules
23 Id. 24 Id. 25 sas.com/insights/analytics/machine-learning.html.
26 Id. 27 Id. 28 Id. 29 Id.
4
of evidence. And there are those who believe that person should be
a trained, licensed attorney. The availability of the
technology raises ethical questions, one of which one author, Wendy
Wen Yun Chang, identifies as “the danger of a failure of
competence.”30 As to lawyers, Chang explains that “in using
technology, lawyers must understand the technology that they are
using, to assure themselves they are doing so in a way that
complies with their ethical obligations — and that the advice the
client receives is the result of the lawyer’s independent
judgment.”31 Lawyers must not “abdicate responsibility” or “blindly
trust the technology.”32 While the technology may appear competent,
its “inner workings are invisible to the naked eye.”33 Even
assuming the user feeds the correct information into the computer,
he or she must still intrinsically trust that the computer is doing
what it says it is doing.34 A lawyer is ethically required not to
blindly accept the answer, and is “trained to perhaps spot
mistakes.”35 Lay persons accessing legal technology, however, have
no such training or protection.36 If an unlicensed person were
performing the same service as the program, it would be called the
unauthorized practice of law.37 Thus, ethical issues appear not
only for lawyers using the technology but also for unlicensed
companies providing legal services to lay people. Chang argues that
“AI legal services should not be permitted to hold themselves out
as providing legal services to lay persons without an actual
lawyer’s involvement and supervision,” and she calls for further
regulation of such technology.38 There is no question that the
computerized research tools employed now, while imperfect, improve
upon the rooms full of books, with supplements and updates, that
some of us used for decades. Whether research “suggestions” will be
commonly beneficial, or the yet-to-come reality of “hard” AI meets
the ideal remains to be seen. AI does not appear poised to replace
experienced attorneys handling complex, sophisticated matters, like
municipal bond packages, large bankruptcies, or securities
litigation, for a few examples.
30 Time to Regulate AI in the Legal Profession? Wendy Wen Yun
Chang, Partner Hinshaw Culbertson. 31 Id. 32 Id. 33
Id.
Despite breathless talk about robot lawyers and machine learning,
few are predicting the imminent arrival of computers that can
employ human factors to think creatively, provide strategic advice,
or even offer wise counsel and empathy. Few are considering
software that can take a deposition, select a jury, or make an oral
argument. Software that assists attorneys in more effectively
deploying those skills through data mining is foreseeable if not
already available from publishers of legal materials. But these
tools still require professional application—they are not self-
driving cars.
34 Id. 35 Id. 36 Id. 37 Id. 38 Id.
ARTIFICIAL INTELLIGENCE AND THE PRACTICE OF LAW OR CAN A COMPUTER
THINK LIKE A LAWYER?
David E. Chamberlain
Timothy B. Poteet
TABLE OF CONTENTS