Artificial Intelligence and Law 10: 227 236, 2002. 2003 Kluwer Academic Publishers. Printed in the Netherlands. 227 AI in law practice? So far, not much ANJA OSKAMP and MARC LAURITSEN Free University, Faculty of Law, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands E-mail: a.oskamp@rechten.vu.nl; marc@capstonepractice.com 1. Introduction As long-time enthusiasts for the great potential of artificial intelligence techniques to transform the practice of law, we are frustrated not to be able to cite any fully unqualified examples of true AI that have been successfully deployed in the real world of law practice. There is as yet no obvious poster child for the field. This is an embarrassing statement with which to start a paper in a special issue like this one, and perhaps it is too harsh. AI and Law researchers continue to work enthusiastically, and there have been experimental applications of AI to legal practice that were rather successful. But the follow up on these experiments has been limited. There are, to be sure, some close cases. Industrial strength systems with legitimate AI pedigrees have been deployed in government social security and welfare contexts, for instance, in Australia, Europe, and the U.S. Some document assembly and other substantive legal practice systems can fairly be regarded as knowledgebased, smart software. And there are presumably AI-related tools at work in law firms and departments that are kept out of public view for reasons of competitive advantage. In this paper we will report on some systems that have found their way into legal practice, either in the experimental phase or in production, and offer an impressionistic (and somewhat dated) overview of the state of this field. This is hardly a comprehensive study, even with respect to the limited number of systems we have encountered. We will also point out some characteristics of the practice world that bear on its amenability to knowledge-based automation. Most of the reasons for the limited success of AI in the legal domain relate to the domain itself and its actors. Then we will describe some initiatives, past and present to build bridges between research and practice. We will conclude with some tentative predictions.
228 ANJA OSKAMP AND MARC LAURITSEN 2. Government systems Before discussing law practice applications more narrowly, it is useful by way of contrast to review a related context in which there has been a substantial number of practically applied AI systems: namely, those that support tasks performed by governmental organizations. Most of the systems mentioned here deal with social welfare or taxation. 2.1. AUSTRALIA The Australian company Softlaw has deployed several expert systems that support the processing of governmental tasks. The systems were developed using rule base technology (STATUTEExpert) targeted specifically for use with legislation and policy (http://www.softlaw.com.au/). They developed expert system applications that form integral parts of major government processing environments. This is how they advertised them on their website: Department of Veterans Affairs the Compensation Claims Processing System (CCPS) is used to process all disability-related claims handled by the Department Comcare - the Initial Liability Module (ILM) is used to process workers compensation claims handled by this agency Department of Defence the Defcare system contains a number of expert system components, supporting decision-making on the key issues in workers compensation: liability, the calculation of weekly payments, and the determination of entitlement to lump sum payments Some of these systems contain very large rule bases that facilitate the exhaustive and consistent application of complex rules. Softlaw claims that deployment of these systems secures substantial improvement in the quality and consistency of decisions. Also, more complex policies can be handled. Their studies showed an improvement in productivity of 80%: more claims can be handled, the processing time is much shorter, and yet less staff is needed. 2.2. THE NETHERLANDS The company MRE, acronym for Master in Expert Systems, has developed and marketed legal expert systems since the early 1990s. The systems are based on decision tree technology and presumably make use of rule-based technology as well. The main domain of MRE s expert systems is social welfare. The systems support municipalities in applying various social welfare legislation, handling very complex administrative tasks. About 60% of the Dutch municipalities have access to one or more MRE programs (Oskamp and Tragter 1997). The effect on quality of the use of these systems is reported in Groothuis and Svensson (2000). They found a substantial number of errors in the decisions of the systems and concluded that although the quality of legal decisions can be improved using expert systems,
AI IN LAW PRACTICE? SO FAR, NOT MUCH 229 those systems do not guarantee legally correct decisions. Yet MRE is well known for the great care it takes in building its systems, involving well known experts both from a theoretical and a practical perspective. They are even leading in some of their domains (Oskamp and Tragter 1997). MRE is presently expanding to other legal domains. MRE is now part of the Dutch publishing company Kluwer. Municipalities in the Netherlands that do not use these ready made systems often have similar systems tailor made. The Dutch national tax department has been using expert systems for handling income tax declarations for some years. Since 1996 Dutch citizens upon request have been provided with floppy disks on which they can return their tax declaration. Since 1997 this has also been able to be done by email. The digitized tax declaration form is a decision tree that guides the user by questions and answers through the form, doing the calculations for him. In this way the tax department has the information in a digital format and thus it can easily perform checks, partly using expert system technology. Present research is using AI methods to develop tools for the whole chain of processes from drafting legislation to its administration by government employees (Van Engers et al. 2001). The United States has also seen a variety of knowledge-based applications that provide information and advice about government benefits. A short, albeit dated, survey of these can be found in Lauritsen (1991). One of the few US-based systems that received attention in the AI literature is MicroMax, a privately sponsored expert system that assists potential recipients and their advocates in analyzing eligibility for a wide range of programs (Lauritsen 1991, 1997). The United States Department of Labor has developed a web-based advisory system called Elaws (Employment Laws Assistance for Workers and Small Businesses). 1 Elaws consists of sixteen separate Advisors, whose coverage includes Employment Standards Administration (ESA), Mine Safety and Health Administration (MSHA), Occupational Safety and Health Administration (OSHA), Pension and Welfare Benefits Administration (PWBA), and Veterans Employment and training Service (VETS). 2 Some federally funded legal aid offices provide web-based expert systems for a variety of legal services. 3 Various courts have begun to offer advisory and form-generation tools for self-represented litigants. See, for example, http://courtlink.utcourts.gov/. 3. Systems in legal practice AI systems developed to support government tasks often quickly achieve extensive use. They may be obligatory or strongly encouraged. Systems for law practice are used on a more voluntary basis. They have to appeal to users who are traditionally not very open to IT, let alone AI. The number of successfully deployed systems is rather limited. We will discuss several examples in this section.
230 ANJA OSKAMP AND MARC LAURITSEN 3.1. LEGAL RESEARCH, DOCUMENT ASSEMBLY, AND WORK PRODUCT RETRIEVAL West Publishing s WIN ( West is Natural ) natural language search tool (Turtle 1995), and comparable offerings from Lexis-Nexis have put some AI-related technologies in the hands of average lawyers. Document assembly tools and related practice systems have a long history in the legal field, and are probably the most broadly distributed knowledge-based applications in law offices today (Lauritsen 1992, 1993, 1999). But even they are used sparsely. Document management systems, litigation support applications, and work product retrieval systems are in more common use, but rarely go beyond conventional relational database and keyword search technology (Lauritsen 1996). A commercial tool used in connection with legal document drafting is Deal- Proof, from Expert East Software (http://www.dealproof.com), which includes a number of tools for proofreading and automatically summarizing documents. 3.2. PUBLISHED SYSTEMS In the Netherlands the publisher Vermande marketed legal expert systems beginning in the late 1980s. These systems were built in a decision tree shell, JURICAS, and were meant for both professionals and laymen. Topics were inheritance law, labor law and penal law (Van Noortwijk 1991). In the early 1990s the system general conditions was published, supporting both the development of general conditions for delivery for companies and evaluating contracts related to these general conditions. This program is now marketed by JIS, a new company for developing software for legal practice (http://www.jis.nl). The Dutch publisher Kluwer has been marketing two expert systems for legal practice. WVP is a system for the settlement of pension rights after separation. OVB is a system for bank tax, answering the question whether such a tax is due and if so calculating how much to pay. Both systems are written for professionals. The shell of these systems is written by Marnix Weusten and Douwe Kracht, while experts in the domain are responsible for the contents of the system. The systems are written in HTML and JavaScript. They ask the user questions and subsequently follow a decision tree to reach their goal. During these questions the user can ask for additional information or look at the legislation and case law by clicking specific links. In the United States, a company called Lawgic has marketed more than 20 expert systems. 4 3.3. EXTRANETS AND WEB SERVICES Several large international law firms have begun to deploy self-help, web-based applications for their clients. These include London-based Linklaters, with its Blue Flag system for derivative transactions, 5 New York-based Davis Polk &
AI IN LAW PRACTICE? SO FAR, NOT MUCH 231 Wardwell s Global Collateral Project, Blake Dawson Waldron (Sydney), with its Virtual Lawyer, 6 and Clifford Chance s NextLaw 7 (Branting 2001; Mountain 2001). An expert system for the formation of Australian companies is commercially available on the Internet (http://www.incorporator.com.au). Its developer describes it as follows: Users answer a series of questions, mostly by selecting from a range of predetermined optional answers. The interview process is intelligent in that the user s answer to each question, or a combination of the user s previous answers, generally determines the next question the user is asked. In this way users are not bothered by any questions that are not strictly applicable to their situation. Also, users are prevented from making errors by an extensive array of stringent field validation measures and associated non-cryptic and informative error messages. Guidance is available, via pop-up windows, to help users appropriately answer any questions about which they are unsure. Virtually all guidance is backed up by reference to relevant sections of the Corporations Law (the Australian companies legislation). All these sections are hyper-linked to the actual section wording of the legislation. Users may check the availability of any proposed company name via a link to the Australian Securities and Investments Commission ( ASIC ) database (ASIC is the relevant government registration authority). 8 An interesting aspect of the Incorporator system is that users only pay for the results of the system if they decide to use the documents. Until that point the system is free. The site uses three client-side interpreted programming languages, namely, Hypertext Mark-up Language (HTML), Dynamic Hypertext Mark-up Language (DHTML) and JavaScript. The documents are generated using Adobe Acrobat s Portable Document Format ( PDF ). LawOnline is a Christchurch, New Zealand, web-based estate planning system (http://www.lawonline.co.nz). 3.4. OTHER EXAMPLES Tax preparation software such as TurboTax is very popular in the United States, as are estate planning and contract drafting programs. Quicken Family Lawyer, by Parsons Technology, and WillMaker, by Nolo Press, are two related examples. In Australia several systems have been built at the Donald Berman Laboratory with the aim of having them used in practice. The results of the laboratory tests have lead to additional grants for commercializing some of these systems. Presently no such versions are on the market. (Stranieri and Zeleznikow 2001 (workshop paper); also see their paper in this special issue).
232 ANJA OSKAMP AND MARC LAURITSEN 4. The law practice domain Why have we yet to see much explicit use of law-specific AI in mainstream legal practice? A few reasons suggest themselves: 1. Law is a complex domain. Much of the knowledge necessary to apply the law is codified in or derivable from written sources. But its application often requires the special skills and knowledge of lawyers. The same knowledge may need to be applied differently in the course of performing different tasks, and from different perspectives. Examples of different roles in the legal domain are those of advisor (consultant), judge or advocate. And an attorney can be for the defendant or for the plaintiff. Different tasks may call for different kinds of support. 2. Doing non-trivial modeling of legal intelligence is hard. We can straightforwardly build little rule bases that encode one logical interpretation of a particularly complex tax provision, or codify the decision tree an expert trial lawyer seems to use in approaching certain tactical decisions. But we understandably shudder at the magnitude of trying, for instance, to capture the elaborate analytical judgement even a young associate brings to the drafting of complex financial documents, or the capacity defense counsel has to frame coherent fact/law answers on the spot in response to questions from a hostile judge. 3. The economic and cultural predicates for AI in conventional legal services delivery are still largely absent, with the dominant ethos of hourly billing and knowledge hoarding. Heavy investments are hard to justify, and lawyers are reluctant to change how they work. 4. Most law practice organizations are preoccupied with infrastructural matters, like keeping the e-mail running, migrating to the latest network operating system or office suite, and converting among word processing formats. Initiatives on the specialized-knowledge or superstructural level often get deferred to next year, which never seems to arrive. 5. To build useful applications that really appeal to practicing lawyers, insight into what lawyers want is necessary. In other words: lawyers must be able to formulate the specifications of the tools they would like to use. But for that they themselves need insight in the potential and limitations of IT and AI. We see that on the one hand lawyers expect too much. They think of tools that could be called robot lawyers performing tasks like looking up legislation and case law on specific topics, combining and analyzing them, and making a case for the lawyer. At present those tasks are too ambitious. On the other hand, if such tools could be built lawyers would be reluctant to use them, since they will not trust them. Trust in less ambitious tools is already a problem, when lawyers don t understand how a system works and produces its output. Lawyers have to see the advantages of using smart tools. One way to achieve this may be to involve them in the research and development of these tools. But if
AI IN LAW PRACTICE? SO FAR, NOT MUCH 233 lawyers are not able to formulate what they really want to use and under which conditions, how can researchers and developers know what to build? Unless we can break out of this vicious circle, it may still be a long while before we will see real AI applications in legal practice. 5. Bridging the gap between research and practice For most of the past fifteen years practicing lawyers and AI researchers appear to have been locked into parallel worlds of theoretically uninspiring implementations and tiny brittle research applications. Robust traffic across that disciplinary divide has yet to develop. As has been stated before, to stimulate this traffic there has to be real interaction between practicing lawyers on the one side and researchers and developers of systems on the other side. This is in our opinion the main problem: until practicing lawyers see clear and immediate benefits of specific applications they will be reluctant to use them. And lawyers who are unfamiliar with the potential of AI will not be able to formulate what kind of tools they would like to use. Although there is no easy way out of this vicious circle, involving practicing lawyers in conferences on this topic and trying to educate them in the field is one way to try. The international conferences on AI and Law have generally not attracted much practitioner interest. Early papers with a practical or commercial bent include Susskind (1987) and Morrison (1989). The 1999 conference in Oslo included a workshop on Automated Document Drafting, and a panel discussion on Artificial Intelligence and Real Lawyering: Where are we in 1999? that discussed the following topics: What are law offices actually doing today, non-experimentally, that can fairly be considered AI Why and why not? Why does AI have such a low profile these days in the legal technology world? What would practitioners like to see the AI research community doing differently? How can theorists and practitioners be more helpful to each other in this field? At the 2001 ICAIL conference in St. Louis a workshop on Legal Knowledge Systems in Action: Practical AI in Today s Law Offices attracted nearly 30 participants. A regional version was held in Chicago in 2002, and a similar event is planned for the 2003 conference in Edinburgh. There is a related series of French-American AI & law conferences see http://www.law.syr.edu/law-and-ai-3/ that have an explicit agenda of making AI and other advanced technologies accessible to average practitioners. The Jurix conferences have been running annually in the Netherlands since 1987 (http://www.jurix.nl). Although efforts have been made to attract legal practitioners, the number of practicing lawyers at each conference is rarely more than a few. An exception was the fifth conference of 1992, held in The Hague and attended
234 ANJA OSKAMP AND MARC LAURITSEN by more lawyers. But the topics of the speakers of that conference were mainly on substantive information law. In 2002 the first LEA (Legal aspects of Electronic Agents) workshop was held in Bologna. This workshop was attended by both computer scientists and lawyers, discussing the topic of intelligent agents. A similar event is planned for 2003, in connection with the ICAIL conference. A discussion form, intended for lawyers and computer scientists about intelligent agents and legal requirements can be found at http://www.iids.org/research/alias.html. Although these conferences have not succeeded in attracting many practitioners, they are known by some of them and the proceedings are at least scanned by those interested and, recently, also by employees of large law firms entrusted with knowledge management. It appears that slowly but surely the first fundaments of the bridge are being built. We hope that these connections will lead to more useful tools for legal practice, and help catalyze a breakthrough in their adoption. Knowledge managers in large firms may be especially useful as intermediaries between the more conservative practicing lawyers and researchers, not only explaining the benefits of existing tools, but also helping the lawyers to formulate the tools they would further want to use. 6. Coming attractions By some standards the impact of AI so far on the practical world of lawyering has been disappointing. But we should not have unrealistic expectations. It s still early. AI researchers and legal practitioners have a lot to learn from each other. And the situation is slowly changing. Use of the Internet is now routine. Lawyers have come to appreciate its potential from private uses, like buying CDs and researching vacation trips. This makes them feel more comfortable with IT and its results. Also the necessity of using technology to manage ever growing streams of information has become clear to lawyers. Some larger firms have hired knowledge managers, sometimes tasked with introducing advanced technologies and exploring knowledge-based e-business initiatives. The Internet has also spurred development of new research tools. The flow of information is so copious that it is almost impossible for human beings to search for it by themselves. Intelligent agents are a longstanding part of AI that is now receiving more attention. They also present many legal issues. These dual dimensions call out for collaboration between computer scientists and lawyers. The LEA workshops are an example of that, but also the ALIAS project, in which AI people and lawyers together try to detect the legal problems that may be caused by the use of intelligent agents and from that perspective try to formulate conditions for developing technologies. 9 Interchanges around these issues may raise lawyer interest in intelligent technologies.
AI IN LAW PRACTICE? SO FAR, NOT MUCH 235 Our instinct is that the now largely disjoint worlds of practical legal technology and academic AI research will find themselves cross-pollinated by a growing corps of border crossers over the next few years, as the commercial relevance of legal AI matures and the usefulness of sustained practical engagement dawns on theorists. The ascendance of knowledge management as a common business discipline in law practice will bring all of this into sharper focus. Dramatic success by some organizations in leveraging expertise through smart technology and innovative management will jolt others into similar action, and we ll be off on a positive feedback cycle that will narrow the gap between artificial intelligence and real lawyering. Notes 1 Accessible at www.dol.gov/elaws. 2 This and several other examples have been taken from an excellent report by Karl Branting, Legal Expert Systems enter the Market place, Workshop on Legal Knowledge Systems in Action, Eighth International Conference on Artificial Intelligence and Law, St. Louis, Missouri, May 2001. 3 Stan Kabala, Poor Residents are Being Offered Free Legal Help, Orange County Register, August 5, 1999, p. B06. 4 See http://www.lawgic.com. 5 http://www.blueflag.com/ 6 Alan Cohen, Legal Advice Without the Lawyers, New York Law Journal, Nov. 15, 1999. 7 IT s Magic Formula Pays Dividends, The Lawyer, May 10, 1999, p. 19. 8 From Macrossan 2001 (workshop paper). 9 http://www.iids.org/research/alias.html References Groothuis, M. M. and Svensson, J. (2001). Expert System Support and Juridical Quality. In Proceedings of JURIX 2000: The Thirteenth Conference, 1 11. IOS Press: Amsterdam. Lauritsen, M. (1991). Knowledge-Based Approaches to Government Benefits Analysis. In Proceedings of the Third International Conference on Artificial Intelligence and Law. ACM Press: Oxford. Lauritsen, M. (1992). Technology Report: Building Legal Practice Systems with Today s Commercial Authoring Tools. Artificial Intelligence and Law 1: 87 102. Lauritsen, M. (1993). Knowing Documents. In Proceedings of the Fourth International Conference on Artificial Intelligence and Law, 184 192. ACM Press: Amsterdam. Lauritsen, M. (1996). Technology Report: Work Product Retrieval Systems in Today s Law Offices. Artificial Intelligence and Law 3: 287 304. Lauritsen, M. (1997). MicroMax at Seven. In Proceedings of the Sixth International Conference on Artificial Intelligence and Law, 253 254. ACM Press: Melbourne. Lauritsen, M. (1999). A Dispatch from the Document Automation Trenches. Workshop on Automated Document Drafting. Seventh International Conference on Artificial Intelligence and Law. Oslo, June, (Available online at http://www.ksg.harvard.edu/subtech2000/laudisp.pdf.) Morrison, Rees W. (1989). Market Realities of Rule-based Software for Lawyers: Where the Rubber Meets the Road. In Proceedings of the Second International Conference on Artificial Intelligence and Law, 33 36. ACM Press: Vancouver.
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