cover pg. - artificial intelligence and the practice of law
TRANSCRIPT
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
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TABLE OF CONTENTS ARTICLE – Artificial Intelligence and the Practice of Law Or can a Computer Think Like a Lawyer? ...... 1-4
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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.
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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.
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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.
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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
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
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TABLE OF CONTENTS ARTICLE – Artificial Intelligence and the Practice of Law Or can a Computer Think Like a Lawyer? ...... 1-4
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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.
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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.
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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.
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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