It is inescapable. Lately there has been a lot of buzz about artificial intelligence (AI). Recently, I came across three articles that caught my attention:
- The Los Angeles Times, “Uber says it will bring its flying taxis to Los Angeles in 2020;”
- Forbes, “Our Driverless Future Begins As Waymo Transitions To Robot- Only Chauffeurs;” and
- KCBA Bar Bulletin, “Driverless Car Law: Coming Soon to a Highway Near You.” FN1
But, before going any further on the topic of AI, I find it is always helpful to get on some common footing. The following are a few helpful definitions of AI.
Merriam-Webster: Artificial intelligence: (1) a branch of computer science dealing with the simulation of intelligent behavior in computers; (2) the capability of a machine to imitate intelligent human behavior.
Wikipedia: Artificial intelligence (AI, also machine intelligence, MI) is intelligence displayed by machines, in contrast with the natural intelligence (NI) displayed by humans and other animals. In computer science AI research is defined as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving.”
Encyclopedia Britannica: Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience.
Definitions aside, for most people thinking about AI brings up notions of robots with human or above-human intelligence. For me it is unavoidable, when I think of AI “The Terminator” and Arnold Schwarzenegger come to the forefront. But AI has a more subtle side and it impacts our lives in many different ways, such as what we see on television, what we read in print (and online), how we commute, our safety and employment, just to name a few.
A recent trip to the dermatologist took an unexpected turn when the doctor expressed his concern that his job would soon be done, and done far better, by AI. As he put it, it would only be a matter of time before a “robot” would be able to remember every inch of the patient and could detect changes that would be impossible for a human physician to detect.
This made me pause. What the dermatologist was expressing was concern about when not necessarily if he would someday be replaced by AI. Similar concerns and events are occurring across industries. Can we as lawyers think we are immune to the possibility that AI will drastically change the legal landscape? Will AI replace attorneys? FN2
In this article I intend to address how AI is impacting lawyers and the legal field directly and indirectly. In examining how it is impacting us directly, I am going to discuss how AI is currently impacting the way attorneys work – a “boots on the ground analysis,” so to speak.
I discuss some ways in which AI will be used in the near future, and I highlight a few companies that are currently marketing their AI technology to attorneys. Then I will briefly turn my attention to how AI is indirectly impacting the law. For this I will mainly be addressing autonomous vehicles and the impact they will have on personal injury attorneys, both for the plaintiffs and the defendants. Finally, I address the lingering question of whether AI is a revolution or evolution.
AI and Its Direct Impact on the Law and Lawyers
It may come as a surprise to some, but AI is already impacting the ways in which lawyers are practicing today, and it is an inescapable reality that its impact on our profession will grow. A recurring theme in AI (or at least in this article) is not if it will impact the legal profession, but when and by how much.
To understand AI and its potential to take over an industry, it is important to discuss Moore’s Law. In 1965, Gordon Moore, a co-founder of Intel, predicted the number of transistors that could be fitted onto a computer chip doubles approximately every two years, and thus its growth is exponential. FN3
If you compare the first microprocessor with today’s model, performance has increased more than 3,500 times; energy efficiency has increased 90,000 times; and price has decreased by a factor of 60,000. To give that some perspective, if cars would have developed at the same rate, they would have a top speed of 300,000 miles per hour, would get more than 2 million miles per gallon, and would cost approximately 4 cents. FN4
Recent studies have confirmed that not only has Moore’s Law remained accurate, but telecommunication and storage of information also experiences exponential growth. FN5 A cell phone’s computational power in 2008 was a thousand times greater and its brain a million times less expensive than all the computing power at MIT in 1965.6
It is such growth of computational abilities that has spawned the potential for human- and above-human-level AI. For example, Watson (IBM’s AI platform that beat the best “Jeopardy” champions of all time in 2011), FN7 is being utilized in the following industries: customer service, education financial services, health, “IoT” (Internet of Things, which is being utilized in the automotive, electronics, energy and utilities, insurance, manufacturing and retail industries), media, and talent. FN8
A recent competition was held on how to make use of Watson, and the winning entry was in the legal field. It utilized Watson to search for relevant evidence in data and predict how helpful the evidence will be in a case. FN9 In their Fordham Law Review article, John McGinnis and Russell Pearce identify five areas that AI will “dramatically change in the near future” – discovery, legal search, document generation, brief and memoranda generation, and prediction of case outcomes. FN10
A quick synopsis of these changes is:
- Discovery – Replacing the junior associate.
*AI’s Current Widespread Usage: Computers utilizing keyword searches that lawyers agree are marks of relevance.
*AI’s Usage Now or in the Near Future: Predictive coding, utilizing computer technicians to help construct algorithms that predict whether a document is relevant. This allows larger datasets to be searched and provides more accurate results. Predictive coding has already been utilized by the U.S. Department of Justice’s antitrust division.
- Legal Research – Replacing the library, improving efficiency, and ultimately cutting costs.
*AI’s Current Widespread Usage: Network analysis evaluating the strength of precedent.
*AI’s Usage Now or in the Near Future: Network analysis identifying the issues within a set of facts and suggesting case law on point. As reported in the article, “How Artificial Intelligence Is and Will Change the Practice of Law,” a bankruptcy attorney in a Miami law firm utilized Ross Intelligence, which leverages IBM’s Watson, to test whether it could out-research him. It took the attorney roughly 10 hours to find an almost identical factual analogous case. Ross Intelligence’s platform found the case almostinstantaneously. FN11
- Legal Analytics – Ultimately affecting the number of cases that go to trial and the amount of discovery.
*AI’s Current Widespread Usage: Rudimentary analysis of similar facts and predictive values and outcomes.
*AI’s Usage Now or in the Near Future: Complex analysis of facts, trends and other large data to accurately predict a case’s outcome. An example of legal analytics already in use is the Supreme Court Forecasting Project. The project was designed by a group of political scientists who created a model of SCOTUS decision-making, based on previous opinions, that more accurately predicted future outcomes than a set of “Supreme Court experts.”
McGinnis and Pearce also address three common objections to AI’s ability to disrupt the legal industry. The three objections boil down to:
(1)Lawyers have always adapted to technological change and it has even increased their incomes;
(2)AI changes will create litigation about their proper scope, thereby creating more demand for legal services; and
(3)Machines can never replace a lawyer’s judgment.
These are rebuffed, in turn, because:
(1)The AI revolution is beginning to substitute for core legal skills unlike changes in the past, and the pace of technological change is faster than ever before;
(2)Most of the costs are transitional costs that will ultimately be relatively settled and the net effect will be a reduction in demand for lawyers; and
(3)Not all tasks modern lawyers perform require much judgment; but more importantly, computers can make judgment calls (think of Watson) and as they improve the ability to do so they will continue to evolve and increase in use.
If you are skeptical of whether AI will be used in the legal profession in ways that infringe on lawyers’ traditional “judgment,” then you may find The New York Times article, “Sent to Prison by a Software Program’s Secret Algorithms,” somewhat alarming.
The article describes a Wisconsin man, Eric L. Loomis, who was sentenced to a six-year prison term, in part because of a report from a private company’s proprietary AI/software program that assessed and generated a report concerning his recidivism risk. The sentencing judge utilized the report when sentencing Loomis.
The program used in Loomis’s case was created by Northpointe, Inc., and the program that generated the report was the Correctional Offender Management Profiling for Alternative Sanctions (“COMPAS”). Loomis’s appeal was heard by the Wisconsin Supreme Court, which took the case on the Court of Appeals’ certified question of “whether the use of COMPAS risk assessment at sentencing ‘violates a defendant’s right to due process, either because the proprietary nature of COMPAS prevents defendants from challenging the COMPAS assessment’s scientific validity, or because COMPAS assessment takes gender into account.'”12 The Court found that, if used properly, no such rights were violated, stating, “because [the] COMPAS risk score was supported by other independent factors, its use was not determinative in deciding whether Loomis could be supervised safely and effectively in the community.” FN13
Clearly, the AI revolution has already begun. The real question is not if, but how soon and to what extent, AI will transform the legal industry. Further, if Moore’s Law continues to hold true, it is only a matter of time before AI infringes on aspects of the practice of law that today many believe unthinkable.
A Quick Rundown of (Some of) Today’s AI Offerings
The following is a sample of current AI products that are being marketed to the legal profession:
*Kira (https://kirasystems.com/): Contract review, analysis and knowledge management. “Kira is intuitive, easy-to-use software to uncover relevant information from contracts and related documents. Kira makes powerful machine learning artificial intelligence accessible to everyone, through an intuitive user interface that features real-timecollaboration and flexible project management.”
*LawGeex (https://www.lawgeex.com/): “The quickest and easiest way for businesses to review and approve incoming contracts.”
- Jury Research and Litigation Support:
*Voltaire (https://voltaireapp.com/): “Harness the power of artificial intelligence and machine learning to generate insights fast. Our technology allows you to access more information than you ever thought possible, in a fraction of the time. Jury research has never been easier. Our proprietary search techniques go below the surface and gain access to information from a variety of sources. Our patent-pending algorithms analyze information from billions of data points and provide you with actionable intelligence on target individuals.” (Utilizes Watson).
- Legal Matter Management,e-Billingand Analytics:
*Legal Tracker (https://www.legaltracker.com/): “Transforming time and money, projects and productivity, outside expenditures.” One of the features allows corporate law departments to compare their departments with others in the industry, giving insight into how their costs, productivity and outcomes stack up.
- Patent Law:
*TurboPatent (http://turbopatent.com/): “Patents made smarter/faster/more affordable …. RoboReview deploys serval expert bots to automatically analyze draft applications for novelty, patentability, antecedent basis, claim support, term consistency and more.”
*Judicata (https://www.judicata.com/): “Judicata is ushering in a new era of legal search that is unprecedented in its precision, relevancy, and simplicity.”
*Ross Intelligence (http://www.rossintelligence.com/): Ask Ross questions in natural language. Revolutionizing search via AI. Firms listed as utilizing this platform: K&L Gates, Bryan Cave, Sedgwick LLP, BakerHostetler, Carlton Fields, Latham & Watkins, and Dentons.
*LexPredict (www.lexpredict.com): Lexsemble – “Designs and develops data-driven legal analytics solutions to help law firms and corporate legal departments extract actionable insight from their data. We draw on deep data science expertise, working with lawyers and other professionals within a company to identify and delineate opportunities for their organization to use data to improve the delivery of legal services. We collaboratively develop relevant data models, utilize novel predictive methods, and design best-in-class visualizations that effortlessly communicate insights gleaned from the data.”
*IBM Watson (https://www.ibm.com/watson/): IBM’s AI platform, impacting multiple industries, including law, as discussed above.
Brief Detour: AI and Its Indirect Impact on the Law and Lawyers – Autonomous Vehicles
AI’s ability to indirectly impact the practice of law is great. One of the most publicized aspects of AI revolution is the development and deployment of autonomous vehicles. The impact automation could have on the legal industry is clear.
According to the Centers for Disease Control, more than 32,000 people are killed and 2 million injured each year in motor vehicle accidents in the United States. FN14 These deaths and injuries in turn equate to an enormous amount of legal work – for plaintiff attorneys, defense attorneys, and insurance claims representatives/attorneys.
No longer limited to science fiction movies, autonomous vehicles are quickly becoming a reality. Classifying a vehicle’s autonomous capability has been standardized across the industry with the SAE International Standard J3016, for automated driving. The SAE classification is as follows:
- Level 0 – No Automation: The full-time performance by the human driver of all aspects of the dynamic driving task, even when enhanced by warning or intervention systems.
- Level 1 – Driver Assistance: The driving mode-specific execution by a driver assistance system of either steering or acceleration/deceleration using information about the driving environment and with the expectation that the human driver performs all remaining aspects of the dynamic driving task.
- Level 2 – Partial Automation: The driving mode-specific execution by one or more driver assistance systems of both steering and acceleration/ deceleration using information about the driving environment and with the expectation that the human driver performs all remaining aspects of the dynamic driving task.
- Level 3 – Conditional Automation: The driving mode-specificperformance by an Automated Driving System of all aspects of the dynamic driving task with the expectation that the human driver will respond appropriately to a request to intervene.
- Level 4 – High Automation: The driving mode-specific performance by an Automated Driving System of all aspects of the dynamic driving task, even if a human driver does not respond appropriately to a request to intervene.
- Level 5 – Full Automation: Thefull-timeperformance by an Automated Driving System of all aspects of the dynamic driving task under all roadway and environmental conditions that can be managed by a human driver.15
Tesla’s “autopilot” (the name it gave to its autonomous driving system) is one of the most widely publicized and well-known systems. Tesla CEO Elon Musk stated in a TED talk last April that Tesla was on track for completing a fully autonomous, cross-country Los Angeles to New York trip later this year.
Other manufacturers, including Audi, Mercedes Benz and Chevrolet, are likewise in an arms race to bring autonomous driving to the masses. One of the primary benefits of automated driving is safety. The goal is to reduce serious injuries to zero. Volvo has reiterated its promise that no one will be killed or seriously injured in a new Volvo by 2020.
These technological improvements will have a drastic impact on the legal profession. (Of course, I am not saying we shouldn’t embrace these changes or that I don’t want these changes to occur.) Notwithstanding, the effects should not be underestimated. Similar AI-driven changes in other industries will likewise have an indirect impact. And remember, once a machine can do something as well as or better than a human, it will quickly replace us.
So then, is there an answer to the question of whether artificial intelligence is a revolution or evolution? Of course there is: It depends.
But more seriously, AI seems more like an evolution, but there will come a tipping point where it most certainly will become a revolution. The real question is not if, but when. And, the when is likely years away, not decades. Waymo, formerly the Google Self-Driving Car Project, has begun testing its fully autonomous vehicles on public roads in the Phoenix area without human safety drivers at the wheel. FN16
Michael Sprangers is an owner and partner of Johnson Flora Sprangers PLLC. His practice focuses on representing those who have been injured as a result of another’s negligence, including professional negligence and negligence resulting in serious personal injury. Sprangers is a member of the ABA and WSBA, and is an Eagle Member of the WSAJ. He is a past presenter at the “Law of Lawyering,” and a graduate of the University of Washington School of Law. He can be reached at firstname.lastname@example.org.
FN1 Editor’s Note: See Michael A. LoCoco, “Driverless Car Law: Coming Soon to a Highway Near You,” KCBA Bar Bulletin, November 2017, https://www.kcba.org/For-Lawyers/Bar-Bulletin/PostId/270/driverless- car-law-coming-soon-to-a-highway-near-you.
FN2 Editor’s Note: See Larry G. Johnson, “When Will a Robot Replace You?” KCBA Bar Bulletin, February 2017,https://www.kcba.org/kcba/newsevents/barbulletin/BView.aspx?Mont h=02&Year=2017&AID=article6.htm.
FN3 https://www.intel.com/content/www/us/en/silicon-innovations/moores- law-technology (last visited Nov. 17, 2017)
FN5 John O. McGinnis and Russell G. Pearce, “The Great Disruption: How Machine Intelligence Will Transform the Role of Lawyers in the Delivery of Legal Services,” 82 Fordham L.R. 3041, 3043 (2014).
FN7 Editor’s Note: Watson was not smarter than Ken Jennings and the other human challengers. It was just faster.
FN8 https://www.ibm.com/watson (last visited Nov 17, 2017)
FN9 McGinnis & Pearce, supra, n. 5, at 3045.
FN10 Id. at 3046.
FN11 “How Artificial Intelligence Is [Changing] and Will Change the Practice of Law,”http://www.21stcentech.com/artificial-intelligence-change- practice-law/ (last visited Nov. 15, 2017).
FN12 State v. Loomis, 371 Wis. 2d 235, 243 (2016).
FN13 Id. at 244.
FN15 https://www.sae.org/news/3544/ (last visited Nov. 17, 2017)
FN16 See, e.g., “Our Driverless Future Begins As Waymo Transitions To Robot-Only Chauffeurs,” https://www.forbes.com/sites/alanohnsman/2017/11/07/our- driverless-future-begins-waymo-transitions-to-robot-chauffeurs/#41290b9ee7e8.