Utilising AI in the legal assistance sector Testing a role for Legal Information Institutes Andrew Mowbray Philip Chung Graham Greenleaf AustLII AustLII AustLII University of Technology Sydney University of New South Wales University of New South Wales Sydney, Australia Sydney, Australia Sydney, Australia andrew@austlii.edu.au philip@austlii.edu.au graham@austlii.edu.au ABSTRACT provision of legal information via the web. Legal Information The use of artificial intelligence (AI) in law has again become of Institutes (LIIs) and the Free Access to Law Movement (FALM),1 great interest to lawyers and government. Legal Information played a very significant role in those developments [1]. What Institutes (LIIs) have played a significant role in the provision of roles might LIIs play in this new AI-oriented environment? legal information via the web. The concept of ‘free access to law’ is The concept of ‘free access to law’ is not static, and has evolved not static, and its principles now require a LII response to the over the past quarter-century [2]. The principles of free access to renewed prominence of AI, possibly to include improving and law now require a LII response to the renewed prominence of AI- expanding free access to legal advice. related developments in law, which could include improving and This paper proposes, and proposes to test, one approach that expanding free access to legal advice, as part of ‘free access to law’, LIIs might take in the use of AI (specifically, ‘decision support’ or consistent with those of FALM’s Declaration of Free Access to Law ‘intelligent assistance’ (IA) technologies), an approach that [3]. ‘Freeing the law’ is a continuous process. leverages the very large legal information assets that some LIIs This paper proposes, and proposes to test, one approach that have built over the past two decades. This approach focuses on LIIs might take in the use of AI (specifically, ‘decision support’ or how LIIs can assist providers of free legal advice (the ‘legal ‘intelligent assistance’ (IA) technologies), an approach that assistance sector’) to serve their clients. We consider the leverages the very large legal information assets that some LIIs constraints that the requirement of ‘free’ imposes (on both the have built over the past two decades.2 This approach focuses on legal assistance sector and on LIIs), including on what types of free how LIIs can assist providers of free legal advice (the ‘legal legal advice systems are sustainable, and what roles LIIs may assistance sector’) to serve their clients. We consider the realistically play in the development of such a ‘commons of free constraints that the requirement of ‘free’ imposes (on both the legal advice’. We suggest guidelines for development of such legal assistance sector and on LIIs), including on what types of free systems. The AI-related services and tools that the Australasian legal advice systems are sustainable, and what roles LIIs may Legal Information Institute (AustLII) is providing (the ‘DataLex’ realistically play in the development of such a ‘commons of free platform) are outlined. legal advice’. We suggest guidelines for development of such systems. CCS CONCEPTS The Australasian Legal Information Institute (AustLII) is providing AI-based services and tools (the ‘DataLex’ platform), • Information systems → Expert systems; Wikis; • Applied which are described, including how they implement these computing → Law; guidelines. A decision support system on rental housing law is to KEYWORDS be developed to implement, test and evaluate the above approach, with the DataLex platform being used by pro bono knowledge-base decision-support systems, legal information institutes, legal (KB) developers from a large law firm to develop the application, assistance sector working in conjunction with a community legal centre that will utilise it, and a university research centre to evaluate the project. 1 INTRODUCTION The use of artificial i ntelligence ( AI) i n l aw, i ncluding i n r elation to 2 DEGREES OF FREEDOM: TRAJECTORIES OF decision-support systems, has again become a matter of great THE DIGITIZATION OF EXPERTISE interest to both the legal profession and to government. The previous wave of enthusiasm for, and investment in, ‘AI and law’ The ‘Web 2.0’ context since about 2004 creates a very different from the early 1980s to the mid-1990s was to a large extent environment from the pre-1995 (pre-Internet, in popular usage) supplanted by the development of the World-Wide-Web and the context of the first wave of ‘AI and law’ This context makes it more feasible to talk about the collaborative development of free legal advice services based on AI. The reasons include the In: Proceedings of the First International Workshop on AI and Intelligent Assistance for Legal Professionals in the Digital Workplace (LegalAIIA 2019), held in conjunction with significant roles that collaboration, in the form of FOSS (free and ICAIL 2019, June 17, 2019, Montréal, Québec, Canada. open source software) and open content (exemplified by Creative Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). 1 FALM website < http://www.falm.info/> – FALM has over 60 members. Published at http://ceur-ws.org. 2 Other LIIs which have built AI-based tools to complement their databases include CanLII/Lexum (now merged). LegalAIIA Workshop, ICAIL ’19, June 17, 2019, Montréal, Québec, Canada Mowbray, Chung and Greenleaf Commons licensing and Wikipedia) have had on the development The results demonstrate that it is becoming viable for professionals of the Internet; the much greater sophistication of interfaces; and to control the representation of their own expertise, as a commons. the possibilities of interaction between AI-based tools and huge amounts of free access legal content. (III) Applying Expertise to Individual Situations. It is the third We can distinguish three types of digitisation relevant to the category, the application of expertise to individual situations (the giving of professional legal advice: representation of information problems of individual clients) via programs, which is seen widely used by experts; representation of expertise and its general as a major threat to the future of professionals and professions [4]. application; and application of expertise to individual situations. At present, the number of convincing examples and their These categories overlap in reality, but these distinctions enable us commercial viability do not make it inevitable that there will be to consider more precisely [4] how likely is it that each category generalised dire results for professions. To understand the likely will become part of a ‘commons of legal expertise’. implications, it is necessary to distinguish at least three types of the programmatic applications of legal expertise: human expertise (I) Representing Expert Domain Information. ‘Raw’ (primary) embodied in knowledge-bases which interact with programs; information used by experts is the most likely aspect of expertise embedded knowledge in artifacts; and machine-generated both to be digitised and to become part of the commons. Databases expertise. The first is most relevant to the provision of legal advice. of primary information essential to legal professionals (legislation, The question is whether, in those areas where legal expertise can treaties, court decisions etc) are already substantially digitised and be effectively captured in knowledge-bases to be used in available online, and with increasing utility (eg smarter retrieval decision-support systems, can they be developed as a commons, or systems, and smarter data structures). In many countries only as commercial products? substantial amounts are available as commons, at least for free access and often as open content, usually via government sources. 3 AN ALTERNATIVE FUTURE: A COMMONS In a few dozen countries such as Australia, free access ‘legal OF LEGAL EXPERTISE information institutes’ (‘LIIs’) aggregate this data and add value to it, making it a resource used by professionals and the general Although there is as yet no obvious tendency toward commons in public alike. Even though some primary information is only relation to the three categories of software-based application of available commercially, in less than 25 years since the start of expertise to individual cases, we argue that this can be encouraged widespread availability of such data via the web, the increase in to develop. Tools for knowledge engineering and for creating free availability is extraordinary, and is tending toward a machine-generated expertise are available as FOSS and are of high comprehensive commons. quality, but the communities of users necessary to develop applications (similar to the FOSS or Wikipedia communities) have (II) Representing Expertise in General Form. When professional not yet developed. We argue that such collaborative alternative expertise is represented (or embodied or reified) this is usually in a could arise primarily from those organisations that seek to provide generalised form which may or may not be applicable to an free legal advice, and be driven largely by their needs, but could individual situation where expertise is needed, because of the expand to involve other participants in the legal profession. enormous variation of individual situations which may arise. It is up to the reader (usually the correct term) to apply the expertise to 3.1 The providers and constraints of free legal the individual situation. Legal professionals represented their expertise in many ways prior to the Internet — in textbooks, advice journal articles, encyclopedias, and in very significant, but more There are many situations where, at least in a country like mundane, forms such as citators and checklists (often as Australia, our social expectation is that legal advice be provided supervisors of non-professionals). The economics of publishing without cost to the public, whether as consumers, citizens or meant that such reification of expertise could rarely be provided as (sometimes) litigants. The organisations most likely to be involved a commons, and instead it usually became an economic asset of a in providing such free3 legal advice are quite diverse, and include commercial publisher and an author. government legal aid providers, community legal centres, The Internet changes some but not all of these factors. Expertise government and community consumer advice centres, specialist remains a very valuable asset which many professionals are NGOs in law-related areas, government agencies giving advice reluctant to embody in any form of commons. However, the last relevant to their functions, and ‘chamber magistrates’ in quarter century has revealed revolutionary potential which is only courthouses. The legal profession, through state and regional Law becoming apparent through the accretion of successes, including Societies and advice centres they provide, and through the free access repositories of current scholarship, archives of extensive pro bono schemes, also contributes. University law published journals, changing academic funding requirements, schools, through their involvement in community legal centres peer-reviewed free content, viral licensing; crowd-sourcing; and internships in other organisations, are potential sources of collaborative editing by closed professional groups; and automated contributors who often have high computing skills. Bodies substitutions for expertise. A ‘closed wiki’ model, where content assisting the legal profession as a whole to avoid liability problems, may only be edited by professionals may be most suitable for law, such as some legal insurers, might also wish to participate. because of its emphasis on authority. Successful commons examples developed by AustLII including multi-author guidebooks 3 ‘Free’ entails ‘free from surveillance’, a test which some commercial providers of [5], and automated citators performing to professional levels [6]. ostensibly ‘free’ services will fail: see [2]. Utilising AI in the legal assistance sector LegalAIIA Workshop, ICAIL ’19, June 17, 2019, Montréal, Québec, Canada A common factor for most of these providers of free legal advice The systems which non-technical legal domain experts are most is that, if they choose to develop AI-related tools to assist their work, likely to be able to develop and maintain are those which represent they will usually have to do so within very constrained development legal knowledge in a way which has a reasonably high level of and maintenance budgets for software or applications. They are isomorphism (one-to-one correspondence) with the legal sources not in a position to pass on such costs to clients, or to purchasers on which it is based, where the representation is reasonably close of applications. Government or other grants for such developments to natural language, and where it is not necessary to prescribe the may provide up-front development costs (at least while the hype order(s) of the procedural steps necessary to reach a solution to a cycle for AI is rising) but will rarely cover ongoing maintenance for problem, but only to declare what legal knowledge is available, applications as the law changes, or technical issues arise. Bringing and leave it to the system to undertake the steps to apply that in out-of-house consultants on specialised software problems, or knowledge. as ‘knowledge engineers’ in relation to particular legal domains, is Fourth, correctly choosing the type of problem where ‘AI and law’ likely to be very expensive. It is therefore a reasonable assumption techniques are most likely to be appropriate is essential. Problem that, at least in the medium to long term, providers of free legal areas based on legislation, or procedural steps, and where there is advice will have to work within significant financial constraints that complexity, will probably give the best results. Problems involving are more severe than those experienced by commercial providers. multiple instances of one factor increase logical difficulty. If it is The implications of these constraints – limited institutional range administratively possible to have multiple organisations collaborate of providers, and limited financial resources – affect the types of to build and maintain a legal knowledge base, this may increase legal advisory systems that it is practical for this sector to develop sustainability. and support. 3.3 The likely roles of LIIs 3.2 Free legal advisory systems: Guidelines for Fifth, we conclude that free access legal information institutes (LIIs) sustainability are unlikely to be the builders of legal knowledge-bases in particular We have previously set out and justified our views on what approach legal domains, because they do not have the necessary in-house to the use of AI tools is most likely to be of value to a free legal expertise in legal subject domains. They have neither the client-base advice service ([7], at 3.1-3.16). These guidelines are based on the that provides a continuing need for such expertise, nor the funds assumptions discussed above of the likely limited financial and to retain such expertise from outside (at least not on a continuing personnel resources of such a service, and on our own lengthy basis, beyond an initial grant). As a result, LIIs are much more likely experience with the DataLex project. They are implemented in the to be the providers of tools by which such knowledge-bases are DataLex platform discussed in the following section. built, the free access legal infrastructure within which they are built, First, the ‘AI and law’ systems that such a service could be and education and support for those organisations that use their expected to find useful are those that justify their answers at least tools and services to build and maintain subject-area applications.4 in part in terms of the formal sources of law. These constraints will In light of that conclusion, we now move to the tools and services mean that only some types of ‘AI and law’ tools are suitable to that AustLII is building. their needs. Second, looked at from the user perspective, which could be 4 AI IN A LII: AUSTLII’S DATALEX that of an employee of a free legal advice service, or perhaps one IMPLEMENTATION of its clients, what counts as a useful level of legal expertise is The Australasian Legal Information Institute (AustLII), through its relative. A system may be valuable to a class of users even though DataLex project ([7] at 2, [8]) is developing tools and infrastructure it has a relatively low point at which it admits that a problem is so as to implement the above ‘sustainable legal advisory systems’ beyond its expertise, and it may serve as a method of triage. In any approach to AI and law in the context of a LII. This platform includes event, it is not realistic to try to build legal expert systems that five main elements, rectangles in the following diagram (Figure 1). encapsulate all the knowledge necessary to answer user problems. The features of each are then summarised. The more realistic aim is to build decision support systems, in the use of which the program and the user in effect pool their 4.1 The DataLex inferencing software knowledge/expertise to resolve a problem. Expertise can and should be represented and utilised by programs in many ways. This means The DataLex inferencing software5 primarily carries out rule-based the knowledge-based system (the knowledge representation and reasoning. It has the following key features: the program) should not be ‘closed’: it must be integrated with • Support for backward-chaining and forward-chaining rule- text retrieval, hypertext and other tools which allow and assist the based reasoning. Rules are expressed in a declarative form. user to obtain access to whatever source materials are necessary to • Rule-based reasoning is supplemented by procedural code, answer the parts of a problem dependent on the user’s expertise. where procedural steps in reasoning are needed. The result is an integrated decision-support system. Third, looked at from the developer perspective, the key 4 Length constraints preclude a survey of what projects other LIIs are undertaking. contextual factor is that user-organisations such as free legal 5 The DataLex inferencing software was originally written by Andrew Mowbray, as advice services, will probably need to both develop and maintain y-sh (‘y-shell’), with subsequent further layers by various authors including Simon their own knowledge-bases, as the only available domain experts. Cant and Philip Chung, to enable web-based operation. LegalAIIA Workshop, ICAIL ’19, June 17, 2019, Montréal, Québec, Canada Mowbray, Chung and Greenleaf 4.2 The AustLII Communities environment – integrating AI with a LII The AustLII Communities environment is used to link automatically both knowledge-bases under development, and advisory systems when in operation, with all of the free access legal materials provided by a LII. The hypertext links in the above knowledge-base extract are inserted automatically, using AustLII’s findacts software, into the knowledge-base as it is written and saved. Further examples of links from applications in operation are given below. 4.3 The DataLex knowledge-base development tools Figure 1: Components of AustLII’s DataLex legal The DataLex development tools [11] are situated within the AustLII inferencing platform. Communities infrastructure. They use a familiar wiki-like editing interface for development and maintenance of knowledge-bases (KBs). Development is within a closed wiki environment. • Rule based reasoning is also supplemented by example-based (or ‘case-based’) reasoning,6 where needed. 4.4 The DataLex user interface • Rules of any degree of complexity may be written, using propositional logic. The DataLex user interface uses the DataLex software and • A quasi-natural-language knowledge-base syntax (ie one knowledge-bases, the linkages provided by the Communities resembling English as far as is possible) is used to declare environment, and user input, to provide legal advisory systems in rules (and examples). operation. • There is no separate coding of questions, explanations and From Figure 3, it can be seen that some of the features of the reports, because they are all generated automatically from interface include: the declared rules, in dialogues generated ‘on the fly’ when • Questions, Facts, Conclusions, and Reports are all generated the system is in operation. This default operation can be from the knowledge-base and user-provided facts, in customised where special circumstances require. understandable form, and are available on screen at all • Isomorphic (one-to-one) relationships between the times. knowledge-base and legislation is facilitated, and assists in • Facts can be deleted (‘Forget?’), and questions then debugging and updating. re-asked; Conclusions can be explained (‘How?’); and • The previous three elements allow easier development, reasons for Questions requested (‘Why?’), generated in the debugging and maintenance by domain experts (lawyers), same manner. without involvement by software experts or ‘knowledge • The system also uses all information available to it, from the engineers’. knowledge-base and user-supplied facts, to suggest other • Collaborative development of larger applications across relevant Related Materials. distributed knowledge-bases is supported. As the consultation continues, conclusions are shown on the An extract from the ElectKB knowledge-base [10] is shown in right-hand side. Selection of a numbered conclusion results in a Figure 2. ‘How’ explanation of that conclusion being presented, as shown in Figure 4. At the end of the consultation, a composite explanation of the final result, and of all the steps necessary for it to be reached, is displayed and may be exported to word processing or other programs for use. 4.5 The LawCite citator and SINO search engine – updating and expanding advice SINO is the open source search engine, developed by AustLII [12], used to operate AustLII and other LIIs. The LawCite citator [6] is an automated international citator for case law and legal scholarship, Figure 2: Extract of a DataLex knowledge-base (or rulebase). accessible to end-users free of any user charges. It is developed and maintained by AustLII in conjunction with a consortium of participating legal information institutes (LIIs). LawCite currently 6 PANNDA (Precedent Analysis by Nearest-Neighbour Discriminant Analysis); see [9] contains index records of the citation histories of over 5.7 million for details about the FINDER (finders’ cases) application of PANNDA. cases, law journal articles, law reform documents and treaties, going Utilising AI in the legal assistance sector LegalAIIA Workshop, ICAIL ’19, June 17, 2019, Montréal, Québec, Canada Figure 3: DataLex user interface features: Consultation, Facts, Conclusions, Related Materials. Figure 4: DataLex ‘How’ explanation during consultation. back to the 1300s. It includes citation records in significant numbers from court decisions in 75 countries. It is integrated fully into the operations of AustLII and other LIIs that use it. The technical details of LawCite are explained elsewhere [13]. The significance of both LawCite and SINO within the DataLex project is that they provide a means of (in effect) expanding the Figure 5: Embedded search link to ‘foreign power’ during scope of a knowledge-base by providing users with access to DataLex consultation. knowledge which is not yet encoded within the knowledge-base. Examples are as follows, from the ElectKB knowledge-base [10] concerning disqualification for eligibility for election to the Australian federal Parliament: The user is then given a list of cases, journal article etc, ranked in default by likely order of relevance, to enable them to determine the correct answer to the question (Figure 6). (a) Wherever the term ‘foreign power’ appears in a consultation (b) Wherever a citation for a case appears in a dialogue, it will dialogue, it does so as a hypertext link which triggers a be linked automatically to the text of the case (where it is a search over AustLII for all occurrences of ‘foreign power’ in neutral citation), with a further link to the LawCite record, the context of s 44 of the Australian Constitution (Figure 5). as in the following example (Figure 7). LegalAIIA Workshop, ICAIL ’19, June 17, 2019, Montréal, Québec, Canada Mowbray, Chung and Greenleaf Figure 6: Search results from embedded search link. significant unmet legal need, as documented in the Redfern Legal Centre (RLC) response ([14]) to [15]. There are four project partners: Figure 7: DataLex automated links to case law references. (1) AustLII is to provide (and further develop) the DataLex platform, including the inferencing software, Communities environment, and underlying legal databases on AustLII, The user is able to note from the LawCite citation record plus software developer skills and knowledge, and project whether that case has been considered by other cases management. subsequent to the knowledge-base being written, and to (2) The Pro Bono & Community Impact program of King and check for any resulting changes to the law. No Wood Mallesons (KWM)8 is to provide lawyers under its pro knowledge-base can be updated as frequently as the law bono program who will work with RLC to build a knowledge- might change,7 and this is particularly so when they are base (‘the application’) in the tenancy law area, using the subject to the constraints discussed in part 3. For example, DataLex platform. the LawCite record for this case alerts the user to recent (3) Redfern Legal Centre (RLC)9 is to provide legal staff and cases considering Sykes v Cleary, that may not yet be taken volunteers working in its tenancy advice practice, to utilise account of in the knowledge-base (Figure 8). the application in its advisory work. It will provide feedback It should be clear from these examples that updating a legal about both the application and the platform, so that they knowledge-base through links and searches requires access to the can be improved iteratively, to KWM lawyers and to case and legislation content of a whole legal system, updated AustLII developers. Once the application is tested by RLC, it continuously. For providers of free legal advice, the most feasible and AustLII will decide whether a version of it can also be source of such information is a free access legal information provided for direct use by the public, via AustLII and institute (LII). through links from RLC’s website. (4) The Australian Pro Bono Centre (APBC)10 at UNSW is to 5 A COLLABORATIVE PROJECT FOR LEGAL provide an independent evaluation of the development of ASSISTANCE LAWYERS AND THEIR the application, and the outcome of the trial of its use. Based on this evaluation it will provide advice to AustLII to assist CLIENTS AustLII to develop a methodology by which the DataLex The next steps of this project will be (once funding is secured) to platform can be more widely applied in the pro bono field to test the approach advocated in this paper will utilise AustLII’s support free access legal advice to the community. DataLex platform to demonstrate how pro bono legal assistance The co-ordinating body for NSW Community Legal Centres programs can result in development and use of shared AI-based has also agreed to examine how it can both assist legal centres legal resources (‘apps’), integrated fully with AustLII’s databases. sharing applications developed using this approach, and assist in The application to be developed concerns NSW tenancy law the identification of which bodies in the legal assistance sector (particularly the Residential Tenancies Act 2010), an area of 7 A knowledge-base maintained by a legislature is a partial exception (would not 8 https://www.kwm.com/en/au/about-us/corporate-responsibility/pro-bono 9 https://rlc.org.au/ include case-law changes). Automated programmatic updating is a formidable task, 10 https://www.probonocentre.org.au/ and unlikely. Utilising AI in the legal assistance sector LegalAIIA Workshop, ICAIL ’19, June 17, 2019, Montréal, Québec, Canada Figure 8: LawCite records for Sykes v Cleary. would be most likely to participate in the development of new to Law (JOAL), 1:1, 2013. https://papers.ssrn.com/sol3/papers.cfm?abstract_id= applications. 2158868. [3] FALM. Declaration on Free Access to Law, 2002-. http://www.falm.info/ declaration/. 6 CONCLUSIONS – WHEN IS AI FEASIBLE [4] Graham Greenleaf. Review essay – technology and the professions: Utopian and dystopian futures. UNSW Law Journal, 40(1):302–321, 2017. https://ssrn.com/ FOR THE LEGAL ASSISTANCE SECTOR? abstract=2973244 or [2017] UNSWLawJl 12. In this paper we have identified why providers of free legal advice [5] Melinda Schroeder (ed) and 70 authors. Northern Territory Law Handbook, 26 July 2016. http://austlii.community/wiki/NTLawHbk/NTLawHandbook. are likely to face significant constraints on the resources available [6] Andrew Mowbray. LawCite Citator, 2008-. http://www.austlii.edu.au/lawcite/. to them to develop and maintain AI-based legal advisory systems, [7] Graham Greenleaf, Andrew Mowbray, and Philip Chung. Building sustainable free legal advisory systems: Experiences from the history of AI & law. Computer and the implications this has for the types of systems they are Law & Security Review, 34:314–326, 2018. pre-publication version at [2017] most likely to use. We have proposed guidelines which will enable UNSWLRS 53. [8] Graham Greenleaf, Andrew Mowbray, and Philip Chung. The Datalex Project: development which is sustainable by the organisations likely to be History and Bibliography, 2018. UNSW Law Research Paper No 18-4. https: providing such advice, and which will contribute to an expanding //ssrn.com/abstract=3095897 or [2018] UNSWLRS 4. commons of legal expertise embodied in AI-based tools. [9] Alan Tyree, Graham Greenleaf, and Andrew Mowbray. Generating legal arguments. Knowledge-Based Systems, 2(1):46–51, 1989. https://papers.ssrn. We have set out the approach that AustLII, through its DataLex com/sol3/papers.cfm?abstract_id=2988931. platform, is taking to facilitate the development of such systems, and [10] Andrew Mowbray. ElectKB knowledge-base, February 2019. http://austlii. how the DataLex approach allows implementation of the guidelines community/wiki/DataLex/ElectKB. [11] AustLII. DataLex development tools, 2019-. http://austlii.community/wiki/ for sustainable legal AI that we have proposed. We have outlined DataLex. a collaborative project to build, test and evaluate both the general [12] Andrew Mowbray. SINO free text search engine, 1996-. AustLII Open source software (Unix/C) http://www.austlii.edu.au/techlib/software/sino/. approach, and an application on rental housing law. [13] Andrew Mowbray, Philip Chung, and Graham Greenleaf. A free access, automated law citator with international scope: The LawCite project. 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