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A legal expert system expresses as a set of formal rules the norms found in the ..... available to guide and control the inferences made by a legal expert system.
Legal interpretation in expert systems Daniel Poulin1, Paul Bratley2, Jacques Frémont1 and Ejan Mackaay1 1Centre de recherche en droit public poulind, fremont, [email protected] 2Département d’informatique et de recherche opérationnelle

[email protected] Université de Montréal c.p. 6128, Succursale A Montréal (Québec) Canada H3C 3J7

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The role of interpretation in law

A legal expert system expresses as a set of formal rules the norms found in the provisions of a statute or regulation, in case law or other legal texts. The process of constructing the system involves interpreting these legal texts and recasting each of them into one or more formal legal rules. The primary sources of law or law-formulations, to use Susskind’s term [Susskind 87, 36-37, 124], must be transformed into law-statements—statements about what the content of the law is—and these in turn must be translated into a formal language as rules of inference which Susskind terms legal productions. These transformations take place outside the context of specific cases, that is without reference to concrete legal problems those rules are designed to solve.

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The construction of a legal expert system involves two conceptual steps: to identify the legal norms that a statute conveys and to express these norms as formal rules. Several strategies have been proposed for this transformation process. Some consist of a rather straightforward transposition of law texts into formal language at the expense of a substantial loss of meaning of the legal concepts involved; others call for a subtler and more complex legal analysis. In all cases, however, what is at stake is the interpretation of legal documents. The problem of interpreting legal documents is well known to lawyers. In legal usage, the term interpretation is employed when the meaning of a legal text, typically a statutory provision, has to be assessed in a concrete situation. In constructing expert systems, one must interpret legal documents ahead of such concrete applications. This interpretation can only be provisional. The best one can do in constructing the knowledge base is to foreclose as few as possible of the meanings for particular provisions one may ultimately want to consider in concrete situations. Conversely, when using the system in a particular situation, one may want to consider different interpretations and their Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is

Proceedings of the 4rd International Conference on Artificial Intelligence and Law, June 15-18, 1993, Computer/Law Institute, Vrije Universiteit Amsterdam, ACM Press, p. 90-99.

argument, general principles of law and arguments from history), teleological/evaluative arguments (the argument from the purpose or from substantive reasons) and what the authors term “transcategorical” arguments (interpretation in conformity with legislative intent, where it can be identified).

consequences before committing oneself to any one of them. A knowledge base should therefore be designed to accommodate several different meanings of any one provision and not be limited to the one that looks most plausible at the time of construction. One might term this a one-to-many representation of knowledge.

The arguments are used in the reasons for judgment. The expression of the reasons varies widely: from a simple subsumptive model through complex or sophisticated subsumption to the discursive alternative justification, “in which the final decision is not presented as a logical consequence of given premises but as the outcome of judicial choices made according to arguments and priority rules” [MacCormick 91, 493]. In countries where this last form of justification is practised the use of different types of argument can be most easily observed. MacCormick and Summers formulate a model identifying general patterns of interaction among the different categories of argument.

A one-to-many representation of knowledge is quite hospitable to the open texture of the law. The precision of most statutory texts may convey to the non-lawyer the idea that legal concepts and provisions are unequivocal and that the only real difficulty is to design a procedure to determine the meaning. For expert systems design, this leads quite naturally to a one-to-one conception, in which each concept has a single meaning and to each statutory provision (lawformulation) corresponds precisely one formal rule (legal production). Lawyers know that such a conception is illusory. Legal concepts are never fully determined. The natural language terms in which the law is expressed are invariably multifaceted. Translation by a single term is likely to be an impoverishment, even though one uses the same term as the legislator. What will be used in the inferences of the expert system are not natural language concepts but symbols belonging to a formal language with precise semantics. 2.

This model is based on earlier work by Wróblewski [84; 88]. Wróblewski’s idea is that the justification of a decision rests on three elements: a set of facts and primary legal rules; a choice justifiable in terms of rules of interpretation; and a set of higher level rules (interpretative meta–rules) and values, which control the application of the rules of interpretation. The work of MacCormick and Summers deals with the contents of such rules of interpretation and higher level rules.

Theories of interpretation in law

To move to a one-to-many representation of legal knowledge, one would hope to draw inspiration from the literature on legal interpretation. Much of this literature has been written by scholars of legal theory interested either in justifying judicial decisions or in proposing reforms. More useful for expert system designers are works, usually aimed at practitioners, that describe in great detail how one goes about interpreting legal texts and what canons of interpretation are used [Côté 91; Maxwell 69]. Even these works, however, have not been written with a view to designing expert systems.

MacCormick and Summers propose an ordering of methods of interpretation. They summarise their model thus: “(a) In interpreting a statutory provision, consider the types of argument in the following order: (i) linguistic arguments; (ii) systemic arguments; (iii) teleological-evaluative arguments; (b) Accept as prima facie justified a clear interpretation at level (i) unless there is some reason to proceed to level (ii); where level (ii) has for sufficient reason been invoked, accept as prima facie justified a clear interpretation at level (ii) unless there is some reason to move to level (iii); in the event of proceeding to level (iii), accept as justified only the interpretation best supported by the whole range of applicable arguments.

A good starting point for expert systems design is the research by the “Comparative Statutory Interpretation Group.” This research took place over the years 1983 to 1990 under the leadership of MacCormick and Summers. Its purpose was to study interpretative practices in nine countries. The results have been published [MacCormick 91], and this publication is our starting point.

c) Take account of arguments from intention and other transcategorical argument (if any) as grounds which may be relevant for departing from the above prima facie ordering.” [MacCormick 91, 531-532] This specification provides a suitable starting point for the formulation of rules and their representation and use by an expert system on statute law. We do not plan to follow the MacCormick/Summers model in all details. Their objective, to account for decision-making and interpretation by the highest courts on the most difficult legal questions, is much broader than ours; the model we develop produces no

A major conclusion of this study is that interpretative practice in the nine countries surveyed, beyond surface differences which can be rationally accounted for, shows substantial similarities. These similarities are evident in the type of argument used. Eleven kinds of argument are identified which can be classified in four broad categories [MacCormick 91, 512 ff.]: linguistic arguments (the ordinary and technical meaning of words), systemic arguments (contextual-harmonization, argument from precedent, analogy with other statutory provisions, logical-conceptual

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novel interpretations. Of the MacCormick/Summers model we retain the idea of hierarchy and ordering amongst interpretative rules. Their detailed description of arguments and their modelling of conflict resolution amongst them will be left for future research. In what follows, we set out a model for representing in a coherent fashion interpretations produced by cases, in scholarly writing and by experts. 3.

Recently, Kowalski and Sergot have discussed the benefits that could accrue from using a richer representation of the legal texts. They remark: “Since our programs can only indicate what follows from one precise interpretation of the law, we need to consider whether an expert lawyer would find such an ability useful”, [Kowalski 90, 212]. While systems using a knowledge base that corresponds to a straightforward reading of the legal texts may be of some utility in the routine application of the law within government departments, assisting more sophisticated lawyers requires less limited systems. This leads Kowalski and Sergot to advocate systems capable of incorporating more than one interpretation, and including a mechanism for maintaining consistency. In their opinion, “These mechanisms can be implemented by metalevel reasoning, by reasoning about the alternative logical models and how they are related to one another” [Kowalski 90, 215]. Routen and Bench-Capon [Routen 91] also envisage using rules at a metalevel to represent facets of the legal texts difficult to reconcile with the usual techniques of logic programming: exceptions, “deeming provisions” (as when x is ‘deemed’ to be y), counterfactuals, and so on.

Knowledge representation: basic choices

An expert system incorporating interpretative models requires new architectures for the knowledge base. Whatever solution is adopted must allow the characteristics of statutory law to be represented correctly. Two current computer paradigms must be combined if the system we envisage is to be implemented cleanly. First, certain elements of the so-called “isomorphic” approach are essential for a viable system. However, this approach must be modified by the addition of a supplementary layer of metaknowledge capable of representing the interpretative model to be implemented. The basic idea of the isomorphic approach is to take advantage of the formalism inherent in legal texts to translate them and formalize them further as executable logic programs [Sergot 86; Bench-Capon 87]. On this view the knowledge engineer follows the legal sources as closely as possible, writing logical propositions that simply paraphrase or reformulate items in the source text. Items are translated quite literally: the sense ascribed to an item is the straightforward reading that would seem evident to ordinary persons, and this straightforward sense is converted into a logical proposition.

The idea underlying multilevel architectures is to distinguish between basic knowledge that concerns the field to be modelled (the object layer), and knowledge that concerns the items in the object layer (metaknowledge). Thus the system has both knowledge about the field of application, and knowledge about this knowledge, or metaknowledge. This idea is not new. As early as 1983, Lenat et al. pointed out how such metaknowledge can be useful: “If metaknowledge is going to be present (and it always seems to be desirable), the knowledge engineer should deal with it explicitly. [...] As a result, the program will function better and will also be easier to build and to modify” [Lenat 83, 222].

This approach is exemplified by the work of Bench-Capon and Coenen. These authors rigorously respect the structure of the source texts. For them, “even an inconveniently structured piece of legislation should have its structure respected” [Bench-Capon 92, p. 75]. To justify this, they claim at least four advantages for the isomorphic approach: for development, the approach “imposes a discipline relatively easy to follow” [p. 70] and allows complex texts to be partitioned into convenient pieces; for validation, it makes it possible to verify the rules systematically; for maintenance, when the law changes, the isomorphic approach facilitates identification of the changes that must be made in the knowledge base; and in use, it is easier to follow the chain of reasoning discovered by the system.

To these advantages, van Harmelen adds that such a system allows the same object level knowledge to serve several ends; that the system is better able to produce explanations of its reasoning; and finally: “[a meta-level architecture allows] the object-level to be purely declarative, without having to worry about procedural aspects. Thus, for any given query, the object-level (implicitly) specifies a set of answers. It is the task of the meta-level interpreter to determine which of these possible answers is going to be actually computed, and in which order.” [Van Harmelen 89, 115]

Of these arguments, the most convincing are those concerning validation and maintenance of the system. It seems evident that strict application of the isomorphic approach would allow the construction of systems that are easy to validate and to maintain, precisely because of the close correspondence between items in the legal text and rules in the knowledge base. Unfortunately, however, this claimed advantage has so far remained purely theoretical, since no useful system has been constructed along purely isomorphic lines.

Despite the interest of such a design, few systems using metaknowledge have so far been presented in artificial intelligence and law. Gardner [87] uses metaknowledge in a straightforward way: it serves to control the inference mechanism, to avoid unnecessary inferences and to introduce hypothetical knowledge. In Prolexs, metaknowledge represented as a classification network provides procedural knowledge [Walker 91].

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rules to be represented separately, leaving us free to express the substantive rules in a fashion that links them to the statute. This separation of the substantive rules coming from the legal text and the other elements of knowledge used in legal reasoning promises among other benefits to facilitate the maintenance of the system when the law changes.

The systems described by Schild and Hamfelt are perhaps the closest to the one we propose. Schild [90] suggests using very general metarules to produce variations of the rules in the knowledge base. These metarules may, for instance, suppress certain preconditions in the old rules to produce new ones. In Schild's opinion the rule base which is thus obtained better reflects the open texture of the rules. In particular, Schild's proposal introduces the idea of including contradictory rules in the knowledge base to reflect opposing points of view.

In the system proposed, a single provision in a legal source may be represented by several rules in the knowledge base. A provision whose meaning is plain and uncontested is represented by just one rule. Provisions that can be interpreted in several ways give rise to as many rules in the object level knowledge base as there are defensible interpretations. Each rule is tagged with a label saying which particular rule of interpretation justifies its inclusion in the knowledge base. It may carry further tags, such as references to the corresponding statutory provision or to related or conflicting rules, perhaps some kind of priority expressing how confidently this interpretation can be sustained, and so on. There is thus a many-to-one relationship between rules in the knowledge base and statutory provisions.

Hamfelt [90; 92] claims that a straightforward translation of the statute text unduly abridges the scope of the legal rules in the statute. He therefore proposes formalizing the principles that allow the law to be interpreted. In his system, legal rules are represented by rule-schemes, from which metarules produce the rules to be applied in concrete instances. Unlike the metarules proposed by Schild, however, those proposed by Hamfelt are derived from the field of application. For instance, he uses a metarule based on argument by analogy. It remains to be seen whether metarules sufficiently precise to produce acceptable legal interpretations can be spelled out.

To illustrate how the proposed system might work, and in particular how rules in the knowledge base may be related, we shall use examples from Canadian unemployment insurance law. In Canada, a worker who loses his job and who satisfies certain admissibility criteria is entitled to unemployment insurance payments. If he leaves his job voluntarily, these payments are in general much reduced. Nevertheless, there are acceptable reasons for leaving a job voluntarily, wich do not entail such penalty. For instance, paragraph 28(4)b of the applicable Act states that an insured worker who accompanies his (or her) spouse to a new residence is generally justified in leaving his current employment. The first example in the figure, rule R1, corresponds to a literal interpretation of this paragraph.

Following this work by Hamfelt, several other researchers have explored the possibilities offered by using metaknowledge in legal expert systems. Breuker and den Haan [Breuker 91], Mariani and a group at the IDG in Florence [Mariani 91; Guidotti 92] and Yoshino and Kakuta [Yoshino 92] have proposed various systems in which conflicts between applicable legal rules are resolved using metarules inspired by such interpretative maxims as “specialia generalibus derogant” (in case of conflict, particular rules have priority over general ones). We propose taking this approach further, by making considerably more extensive use of metaknowledge. 4.

Levels of legal knowledge

In several decided cases, judges have allowed exceptions to the “acceptable reasons for leaving a job voluntarily.” We examine two such cases, which provide us with an example of conflicting rules. In one case the judge, taking a literal view of the law, decided that when a soldier is posted to a new station, this does not constitute a change of residence in the legal sense, and that therefore his wife is not justified in voluntarily leaving her employment to follow him (Canadian Umpire Board, CUB-45). Rule R2 in the figure reflects this interpretation. Later, a different judge arrived at a different conclusion by taking into account the purpose of this paragraph of the Unemployment Insurance Act, and the facts that were before him. In this second case, the soldier's wife had found a letter from another woman in her husband's clothes. In the circumstances, the judge decided that she was justified in leaving her job to follow her husband. Furthermore, he gave as his opinion that following one's spouse to a new military posting is sufficient reason for leaving a job if otherwise the family situation might be endangered, (CUB-5938). Rule R3 in the

Starting from the interpretative models mentioned previously, we propose to design a system that reflects more faithfully than previous designs the nature of legal reasoning, in that it allows the possibility of differing interpretations of the law. We are convinced that much is to be gained if the isomorphic approach is enriched by the use of metaknowledge and by incorporating a rich interpretative model. In the areas which concern us, the law changes frequently [Bratley 91], and this ‘volatility’ cannot be ignored. So far only the isomorphic approach offers hope of mastering this volatility, but it has the disadvantage of permitting only an oversimplified representation of the law. It is for example difficult using the isomorphic approach to introduce into the rule base other knowledge necessary when the rules are applied, such as heuristic knowledge gleaned from experts, or their procedural expertise. In the system we propose, the use of metaprogramming allows heuristic and procedural

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figure illustrates this interpretation. This example involves opposing rules based on premises which do not conflict; other examples could be added of rules that are directly contradictory, in the sense that they arrive at opposite conclusions from the same statutory provisions.

a) General The interpretative models mentioned above can be expressed formally in the metalevel and thus be made available to guide and control the inferences made by a legal expert system. They can be used in a general way to provide a framework for the inference process and to reduce the search space. In particular, they can be used to control the inference process when the rule base includes contradictory formulations of the judicial constraints. They also serve to weigh the persuasive force of arguments: one may be based on the most likely interpretation, another on a less likely but still plausible one, and so on. Finally the interpretative models implemented in the metalevel are invaluable as an aid to producing explanations and justifications of the legal arguments thus constructed.

The existence of such rules raises the question of the coherence of the rules in the object level knowledge base. What we propose allows several meanings to be represented for a single provision of law. Should we not therefore fear that the system will contain contradictory rules, and collapse? Fortunately such fatal contradictions can be avoided. For while representing the full semantic richness of the source texts means including contradictory rules at the object level, yet when a chain of reasoning is constructed, the metarules controlling the inference process can be designed to avoid appealing in the same argument both to a rule and its opposite. Thus each individual argument produced will be coherent. Nevertheless by invoking different rules at the object level, the metalevel rules may be able to construct complete and coherent arguments in support of a particular conclusion as well as against it.

The interpretative model proposed by MacCormick and Summers that we saw earlier can be expressed in the form of a metarule that imposes a particular sequence on the analysis of a legal question. In the system we propose, such a metarule would force the system to consider first those rules obtained by a linguistic analysis of the law; next the rules included on systemic grounds, and finally any remaining rules. The rule called MacCormickSummers in the figure illustrates this progressive widening of the interpretations. In particular, the filter theories/3 applied to the object level rules at first accepts only those rules corresponding to a literal interpretation (see line 3). Subsequently, at lines 5 and 7, the filter is widened so that the analysis can be continued using rules obtained from other interpretative points of view.

A lawyer uses many types of knowledge, substantive, interpretative, procedural and common sense. If these different types of knowledge are tumbled pell-mell into a single mass of rules, confusion follows. Using several levels of knowledge allows the situation to be represented much more clearly. While the first level of the knowledge base holds the substantive rules stemming from the legal texts in question, the second level represents the lawyer’s other knowledge. Rules at the object level concern actions to be taken and states of affairs in the world outside the system; the metarules, on the other hand, concern actions to be taken and states of affairs regarding the rules in the object level. Metarules impose a certain order on object rules to arrive at coherent readings of the law.

b) Procedural Applying a legal text requires more than the ability to produce one or more acceptable interpretations. A legal expert system must also include representations of procedural and methodological knowledge related to particular situations. The lawyer knows, for instance, that he must first determine whether the current situation falls into some particular class, whether some particular provision of the law applies in this case, and so on. Knowledge of this type reduces the search space, and helps organise the dialogue with the user. However it cannot conveniently be incorporated within the object level rules. In the isomorphic approach, the principle that the structure of the object level rules should correspond to the structure of the legal texts provides no guidance as to how these rules should be used.

From the computer scientist’s point of view, variables in the metarules can be bound not only to objects in the world outside the system, but also to rules or even sets of rules from the object level. When the metarules call the inference mechanism, they will pass to it a subset of the object rules, chosen using the tags assigned to the object level rules. The subset may, for example, include only the object level rules acceptable in a particular style of interpretation. As mentioned earlier, the subset can be chosen, too, so as to avoid including contradictory object level rules that would allow the inference mechanism to generate unacceptable conclusions. In fact, using metarules allows us to endow the system with some of the lawyers’ intuitive knowledge about how to apply legal rules. The system thus makes better use of substantive legal rules, since besides the standard strategies implemented in its inference engine it has access to metarules which express different facets of a jurist's “general, procedural, adversarial and inferential” expertise.

Several advantages arise when procedural knowledge is separated from the representation of the rules. Aiello [88, 246-247] points out that if the way the rule base is to be applied is encoded explicitly at the object level, then this single use is the only one possible. It is preferable to maintain the generality of the rule base. However ‘general’ rules cannot easily be used in practice unless the system incorporates procedural knowledge, represented here at the metalevel. Furthermore a rule base free from control information, designed straightforwardly to represent the juridical provisions and structured in the same way as the

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metalevel must implement a similar strategy for using the object level knowledge.

legislative text, is easier to modify as the law evolves than one where other considerations, such as control of the inference mechanism, complicate the meaning of the rules.

In fields where the law is determined by case law rather than by statute, a number of researchers have described systems able to reason for both sides of a question. Such systems usually employ case-based reasoning [Rissland 87; Ashley 90]. Ashley, for example, describes the interest of such systems thus:

The required sequence of analyses needed to establish admissibility in the general case can serve to illustrate the kind of procedural metarule needed in our system. One such procedural metarule is Gen_qualification (see the figure). Such a metarule, when used in backward chaining, involves the analysis successively (lines 4 to 8) of interruption of earnings, the establishment of the qualifying period and of the number of weeks of insurable employment, and finally the application of the qualifying test. If the result of these analyses is clear, that is, if the claimant's eligibility has been established without having recourse to rules that may be contradicted, then we are finished; otherwise the rule Gen_qualification makes the system try to establish nonqualifying (line 9).

“Designers of expert systems in all fields need to focus on building systems that present alternatives. To many, a computer is a machine that accepts a question and returns the answer. […] That model does not work in a domain where there is no right answer and where the most important function of a computer is to assist, not supplant, the decision maker by providing a range of alternative reasonable courses of action.” [Ashley 90, 4-5]

c) Adversarial Much as for procedural knowledge, we propose using metaknowledge to represent specific strategies of argument that can be employed depending on the point of view of the user. In a legal knowledge base representing only one interpretation of the law, such ‘points of view’ are unthinkable, and whatever line of argument the user wishes to adopt, the result is the same. In the system we propose, the presence of alternative rules and of differing interpretations allows us to produce different inferences starting from the same facts. Flexibility at the metalevel is employed to produce inferences favourable to one or the other of the parties involved. Consider, for example, the law concerning benefits paid by the government to individuals. It is to be supposed that the people administering the law favour careful use of public funds, so they will try to avoid giving money to anybody not entitled to it. On the other hand, voluntary associations whose aim is to defend the beneficiaries of those payments will try to maximize the amounts paid to their members. Although both parties found their arguments on the same statutory texts, there is frequently a considerable difference between the interpretations of these texts that they advance. Moreover often, if not always, the lawyer for one of the parties, even if he is convinced he should win, does not stop his examination of the case on discovering the first argument he can use in his favour. On the contrary, even when he believes his case to be strong, he will want to know what counterarguments can be advanced against it, so he may prepare a rebuttal. The rules of inference at the

However in the area of statute-based law little work has been done on such systems. Rissland and Skalak have described the CABARET system, a combination of a rulebased and a case-based system, able to argue either side of a question [Rissland 89; Skalak 92]. In their opinion, casebased reasoning is preferable for a faithful representation of incompletely defined concepts and of the multiple interpretations to which these can give rise. This, they observe, is because when faced with indeterminacy in the law, only the courts can settle the issue: “In particular, one tries to resolve interpretation problems by considering past applications of the rules and terms in question: by examining precedent cases, comparing and contrasting these with the instant case, and arguing why a previous interpretation can (or cannot) be applied to the new case.” [Rissland 89, 46] For our part we propose that the choice of an objective and the savoir-faire associated with handling opposing points of view should also be expressed in the form of metarules. One example of the formulation of opposing points of view can be seen in the rules Claimant and Gvt (see the figure). These express respectively the hypothetical points of view of the insured worker and of the administrators concerning an

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Examples of rule and meta-rule

-- Object rules r(R1,context(link(28,4,b,-,-),_, theories(ling(‘ordinary meaning’,CUB-45,CUB-7451]),-,-), high), justification_accompaning_a_spouse(CLAIMANT,true)):spouse(CLAIMANT,SPOUSE), moving(SPOUSE), spouse_moving_exception(CLAIMANT,SPOUSE,false). r(R2,context(link(28,4,b,-,concept(“home”)),rel_rule(-,-,con([R3]),-), theories(ling(‘ordinary meaning’,[CUB-45]),-,-), normal), spouse_moving_exception(CLAIMANT,SPOUSE,true)):military(SPOUSE), new_military_posting(SPOUSE). r(R3,contexte(link(28,4,b,-,-),rel_rule(-,-,con([R2]),_), theories(-,-,teleologic(‘section goal’,[cub-05938])), weak), spouse_moving_exception(claimant,spouse,false)):military(SPOUSE), new_military_posting(SPOUSE), threatened_family_home(CLAIMANT,SPOUSE). -- General meta-rule mr(“MacCormickSummers”, type(“gen”),rel_mr(analog([“PAC”]),adv(_)), goal(GOAL, RESULT)):analyse(r(_,context(_, _,theories(_,n,n),_),_),GOAL,Tree_L), if clear(Tree_L, RESULT); else analyse(r(_,context(_, _, theories(_,_,n),_),GOAL,Tree_S), if sound(Tree_L, Tree_S, RESULT); else analyser(r(_,context(_, _,theories(_,_,_),_),GOAL,RESULT).

1 2 3 4 5 6 7

-- Procedural meta-rule mr(“Gen_qualification”,type(procedural),rel_mr(analog(_),adv(_)), goal(general_qual, RESULT)) :read_fact(qualifying), analyse(r(_,_,_), interruption_of_earnings,_), analyse(r(_,_,_), qualifying_period, _), analyse(r(_,_,_), weeks_of_ins_employment, _), analyse(r(_,_,_), qualification_test, T_Q), if clear(T_Q, RESULT_Q); else analyse(r(_,_,_), nonqualifying, T_NQ), if clear(T_NQ, RESULT_NQ); else synthese(gen_qual, RESULT_Q, RESULT_NQ, RESULT).

1 2 3 4 5 6 7 8 9 10 11

-- Adversarial meta-rule mr(“Claimant”, type(“adversarial”),rel_mr(analog(_), adv([“Gvt”])), goal(qualifying, RESULT)) :analyse(r(_,_,_), general_qual, RESULT).

1 2 3

mr(“Gvt”, type(“adversarial”),rel_mr(analog(_), adv([“Claimant”])), goal(qualifying, RESULT)) :analyse(r(_,_,goal(_,true)), disqualification, Analyse_Ex); if clear(Analyse_Ex, RESULT); else analyse(r(_,_,goal(_,true)),nonqualifying, Analyse_In); if clear(Analyse_In, RESULT); else analyse(r(_,_,_), general_qual, RESULT)).

1 2 3 4 5 6 7

Note : These rules do not come from a working system. They are intended simply to illustrate how we propose to use various kinds of legal metaknowledge. unemployed person's payments. Although

admissibility for insurance the example is perhaps

oversimplified, it nevertheless illustrates the possibility of representing the existence of differing points of view on some question. In the Gvt rule, the first considerations to be analysed are those that might disqualify a claimant. A

Proceedings of the 4rd International Conference on Artificial Intelligence and Law, June 15-18, 1993, Computer/Law Institute, Vrije Universiteit Amsterdam, ACM Press, p. 90-99.

very different approach is adopted in the Claimant rule, which supposes that the insured worker or an organisation representing him will first try to prove his admissibility. Notice that since opposing rules may be present in the base, implementing different points of view in this way may well lead to establishing differing conclusions. d) Inferential Experienced lawyers know how to cope with the ambiguity inherent in legal rules. A legal expert system must therefore also be able to function coherently in the face of ambiguity. First, it must be capable of giving a plain answer based on the most evident, straightforward reading of the law. In the field mentioned above, concerning government benefit payments to individuals, it is often clear to everybody involved that x is entitled to such-and-such a payment, and that y is not. Even when the knowledge base incorporates different interpretations of the statutory rules, such plain answers must be possible. Hence the system must know which rules represent on the face of things the most evident readings of the legal texts. It must also be able to build alternative chains of reasoning in cases where no single, obvious answer can be found, and to produce an argument supporting a predetermined point of view. To achieve this, the system must be provided with metarules that can identify the points in an argument where a different course might have been taken, and that can indicate the consequences of following the alternative path. With such a mechanism, the system will be able to produce alternative inferences leading to different conclusions. Finally it must be capable of explaining and justifying the inferences it has made in any particular case in terms of the interpretative model used. 5.

Overview of the proposed system

At the outset, the user will be invited to define the particular problem to be considered, and the task of the system. For instance, if it is a question of determining a claimant's admissibility, the system may be asked to produce the most plausible analysis, or to look for arguments supporting either a positive or a negative answer. For the purpose of this example, suppose the user is a civil servant whose job it is to examine a client's dossier, and that he adopts the attitude outlined above, namely to analyse first the reasons why he should refuse admissibility. The rule to be used for an analysis from this point of view is the rule Gvt. Suppose next that the system is informed that the insured person left his job to follow his spouse to a new residence. Several object level rules that set out criteria found in the jurisprudence therefore become applicable. One of these, rule R1, states that, with certain exceptions, leaving a job in order to follow one's spouse to a new residence is justified. Considering the exceptions to this rule will allow us to illustrate the role of the general metarules.

One of these general rules, the MacCormickSummers metarule, will guide the system in its use of conflicting object level rules by specifying the order in which rules resulting from different types of interpretation are to be considered. Two different object level rules establish different conditions for a spouse_moving_exception. The MacCormickSummers metarule will lead the system to prefer the rule obtained on straightforward linguistic grounds (R2), rather than the rule obtained by consideration of the aims of the law (R3). In this example, when rule R2 is brought into play, and the system is informed that the spouse in question is in the Army, the conclusion will be reached that the claimed justification does not apply (see rule R2), and that therefore the claimant is not entitled to benefits. However a second phase of analysis is possible. The inferential rule controlling the system will offer the user the opportunity to explore the opposing point of view. In other words, it can suggest arguments that might be opposed to the analysis just produced. This second analysis may be carried out in several ways, two of which we shall look at. First, the tags concerning similar rules and opposing rules (analog et adv) attached to the metarules can be used to identify a metarule that expresses a different point of view to the one just used. In our example, using the attribute adv of the metarule Gvt the system can discover the metarule Claimant which formalizes a point of view more favourable to the insured person. The inferential metarule can thus try Claimant and the user will be supplied with a new analysis, possibly more favourable to the worker. The second approach for exploring opposing points of view also uses the relations between rules, but this time it is the relations between object level rules, not between metarules, that are important. In this approach the proof tree—the record of what inferences were made—is examined, and for each rule used, the attributes giving contradictory or opposing rules (con and opp) are consulted. In this way rules that might lead the analysis to a different conclusion are discovered. In our example the relational attributes of rule R2 indicate that there exists a rule R3 whose effect is the opposite. This rule can be used to try to prove that the spouse_moving_exception does not apply, and that consequently the worker's decision to leave the job is justified. More generally, the system can use all the contrary rules that it finds to try to produce a second analysis, once again more favourable to the claimant. This example, though greatly simplified, will, we hope, serve to illustrate how the different types of metaknowledge will be used. The proof that they can perform as we claim will only be available, of course, when we finish our current project to implement a system incorporating not only various sorts of metaknowledge but also a knowledge base that includes representations of contradictory legal rules.

6.

Relation to other research

The idea of using theories of interpretation in expert systems to capture more of lawyers’ reasoning is not new with us. Bing [91] deplores that no effort has been made to represent in legal knowledge bases the internal legal rules operating on the substantive rules. Others, while relying on interpretative theories, have sketched systems that could accommodate some elements of such theories. Gordon [91] proposes a "Truth Maintenance System" capable of accommodating “alternative” interpretations of legal texts. Prakken [91] hopes to use logic to model disagreement on legal questions. Oskamp [89] proposes using metaknowledge to co-ordinate the use of rules from different sources: expertise, case law, scholarly writings and legislation. Finally Schild [90] proposes using several possibly contradictory rules to capture the "open texture" and the adversarial character of the law. Several researchers have drawn on theory developed by legal scholars to design systems mimicking operations particular to legal reasoning: Gardner [87], McCarty [83; 91] and Branting [91]. This is not to say that expert systems developed along more traditional lines take no account of legal theory. The Nervous Shock Advisor [Smith 87], Latent Damage Advisor [Capper 88] and Mairilog [Bourcier 90] are there to show the contrary. But neither the first group nor the second specifically incorporate an interpretative model in their designs. Very relevant to what we propose here is the work that explicitly deals with the interpretation of legal concepts or that relies on metaprogramming to reflect interpretative rules. Rissland and Skalak use cases to produce arguments about the interpretation of statutes [Rissland 89; Skalak 92]. They propose a case analysis method and arrive at similarity indexes between a hypothetical case and those already known to the system. From these similarities it is possible to construct different arguments about what the law is in a given case. Ashley [90] takes a similar approach in his HYPO system. Hamfelt [90; 92] was the first to develop a system using different levels of knowledge to simulate the effect of rules of interpretation on substantive legal rules. His system uses metarules (the rules of interpretation) to derive substantive rules from rule-schemes. Hamfelt feels that it is even possible to set up rule-schemes which express general interpretative rules, and from which particular interpretative metarules can be derived. Besides Hamfelt, others have described systems using metaknowledge. Breuker and den Haan [91] proposed using metaknowledge to resolve conflicts between rules arising when the system is applied to a formal representation of the legal situation under consideration. A group of researchers in Florence [Mariani 91; Guidotti 92] have also designed a system that uses metaknowledge to produce the effect of interpretative

metarules. Yoshino and Kakuta [Yoshino 92] propose a similar solution for implementing criteria of validity and priority among the substantive legal rules. Conclusion Constructing the knowledge base for an expert system involves the interpretation of legal texts. This interpretation, while taking place ahead of concrete legal cases, is not fundamentally different from the kind that lawyers engage in during lawyering. When lawyers raise the issue of interpretation, they usually wish to argue that several interpretations can plausibly be given to a legal text. Expert systems designs have not so far been hospitable to this view. Most rule-based systems are constructed on the premise that for any statutory provision or set of provisions there should be only a single formal rule in the knowledge base. Allowing several formal rules to correspond to a single set of legal source material would lead to incoherence. In many systems, the “single translation” view is combined with the isomorphic approach, which holds that the source material should be chosen in units coinciding as much as possible to single statutory provisions. The isomorphic approach is particularly helpful for the maintenance of expert systems when the underlying law changes. This paper proposes a model to accommodate in an expert system a plurality of meanings for a statutory provision or other unit of legal source material, while maintaining some of the advantages of isomorphism. The model draws its inspiration from work by MacCormick and Summers on interpreting statutes, which recognises hierarchy and order among rules of interpretation. In our model, the expert system uses two kinds of rules: the usual or lower level rules, which translate substantive law, and metalevel rules delimiting the set of these lower level rules that can be called upon during the inference process. This allows the system to produce different and possibly contradictory interpretations of a statutory provision, each of which is in itself complete and coherent. We envisage several kinds of metalevel rules: general, procedural, adversarial and inferential. They correspond to different kinds of intuitive knowledge lawyers draw on. The introduction of metarules not only allows us to accommodate several, possibly conflicting meaning of legal provisions within a single knowledge base, but also clarifies the explanations the system can provide a user in accounting for its conclusions. The system should nonetheless come to unambiguous conclusions in straightforward cases. While several researchers have discussed metaknowledge or have brought it into their models, none, to our knowledge, has used it to accommodate multiple interpretations of legal norms.

Acknowledgements

[Capper 88] Capper, P. and Susskind, R.E., Latent Damage Law – The Expert System, London: Butterworths, 1988.

The work described here is supported by grants from the Social Sciences and Humanities Research Council of Canada (#410-92-1858) and the Fonds FCAR of Québec (#93-ER-1557).

[Côté 91] Côté, P.-A., The Interpretation of Legislation in Canada, Second Edition, Cowansville Québec: Éditions Yvon Blais, 1991; (Translation of

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