On Legal Teleological Reasoning

Given a common pool of facts and legal rules, Judges on a panel may form different justifications for decisions, which are then voted upon. It is clear that a Judge’s personal values and purposes play in developing their opinion, which is a form of teleological reasoning. The paper introduces the Value-based Formal Reasoning (VFR) framework, which describes how a Judge’s personal values can be used in the construction of a justification for a decision

Argument Schemes for Reasoning with Legal Cases Using Values

ABSTRACT Argument schemes can provide a means of explicitly describing reasoning methods in a form that lends itself to computation. The reasoning required to distinguish cases in the manner of CATO has been previously captured as a set of argument schemes. Here we present argument schemes that encapsulate another way of reasoning with cases: using preferences between social values revealed in past decisions to decide cases which have no exact matching precedents when the cases are described in terms of factors. We provide a set of schemes, with variations to capture different ways of comparing sets and varying degrees of promotion of values; we formalise these schemes; and we illustrate them with some examples

A methodology for designing systems to reason with legal cases using Abstract Dialectical Frameworks

This paper presents a methodology to design and implement programs intended to decide cases, described as sets of factors, according to a theory of a particular domain based on a set of precedent cases relating to that domain. We use Abstract Dialectical Frameworks (ADFs), a recent development in AI knowledge representation, as the central feature of our design method. ADFs will play a role akin to that played by Entity–Relationship models in the design of database systems. First, we explain how the factor hierarchy of the well-known legal reasoning system CATO can be used to instantiate an ADF for the domain of US Trade Secrets. This is intended to demonstrate the suitability of ADFs for expressing the design of legal cased based systems. The method is then applied to two other legal domains often used in the literature of AI and Law. In each domain, the design is provided by the domain analyst expressing the cases in terms of factors organised into an ADF from which an executable program can be implemented in a straightforward way by taking advantage of the closeness of the acceptance conditions of the ADF to components of an executable program. We evaluate the ease of implementation, the performance and efficacy of the resulting program, ease of refinement of the program and the transparency of the reasoning. This evaluation suggests ways in which factor based systems, which are limited by taking as their starting point the representation of cases as sets of factors and so abstracting away the particular facts, can be extended to address open issues in AI and Law by incorporating the case facts to improve the decision, and by considering justification and reasoning using portion of precedents

Interpretive Interactions among Legal Systems and Argumentation Schemes

This thesis is about argumentation schemes that help to deal with interactions between national and foreign canons of interpretation in private international law cases. In fact, many legal orders, like Italy, require that, in conflict of laws disputes, courts apply the relevant foreign law using canons of interpretation and rules of application of the original foreign system. Our research hypothesis is that, in interpreting the foreign rule, domestic courts incur interpretive divergences of many kinds among the involved legal systems. Foreign law interpretation may result in linguistic and/or conceptual misalignments, in normative and/or interpretive gaps, and in specific incompatibilities between inner and foreign canons of interpretation. By focusing on interpretive conflicts within one legal system, legal theorists and AI and Law scholars have not yet paid sufficient attention to the issue, even if pluralist logics and argumentation have been generally applied to legal pluralism and conflict of laws. The present study fills this gap in the literature: it explores the feasibility of a theory for arguing and interpreting in private international law contexts, providing an argument-based conceptual framework that encompasses plausible interpretive interactions. To this end, and after addressing the epistemic concerns foreign law raises for domestic judges, the thesis gives a definition of cross-border interpretive incompatibilities and proposes argumentation schemes to reason with interpretive canons coming from different legal systems. An illustrative list of critical questions is used to evaluate the correctness of such interpretive reasoning. Lastly, the thesis presents the first formal developments of the study, based on the concept of meta-argumentation. It is possible to detect two main contributions to knowledge. First, this work identifies the components of foreign law interpretation, an interpretation activity with significant practical implications for legal systems today. In so doing, it also indirectly contributes to better understand interpretation at large. Secondly, its argument-based analysis paves the way for further formal applications in the domain of AI and Law

Representation Of Case Law For Argumentative Reasoning

Modelling argumentation based on legal cases has been a central topic of AI and Law since its very beginnings. The current established view is that facts must be determined on the basis of evidence. Next, these facts must be used to ascribe legally significant predicates (factors and issues) to the case, on the basis of which the outcome can be established. This thesis aims to provide a method to encapsulate the knowledge of bodies of case law from various legal domains using a recent development in AI knowledge representation, Abstract Dialectical Frameworks (ADFs), as the central feature of the design method. Three legal domains in the US Courts are used throughout the thesis: The domain of the Automobile Exception to the Fourth Amendment, which has been freshly analysed in terms of factors in this thesis; the US Trade Secrets domain analysed from well-known legal case-based reasoning systems (CATO and IBP); and the Wild Animals domain analysed extensively in AI and Law. In this work, ADFs play a role akin to that of Entity-Relationship models in the design of database systems to design and implement programs intended to decide cases, described as sets of factors, according to a theory of a particular domain based on a set of precedent cases relating to that domain. The ADFs in this thesis are instantiated from different starting points: factor-based representation of oral dialogues and factor-based analysis of legal opinions. A legal dialogue representation model is defined for the US Supreme Court Oral Hearing dialogues. The role of these hearings is to identify the components that can form the basis of an argument that will resolve the case. Dialogue moves used by participants have been identified as the dialogue proceeds to assert and modify argument components in term of issues, factors and facts, and to produce what are called Argument Component Trees (ACTs) for each participant in the dialogue, showing how these components relate to one another. The resulting trees can be then merged and used as input to decide the accepted components using an ADF. The model is illustrated using two landmark case studies in the Automobile Exception domain: Carney v. California and US v. Chadwick. A legal justification model is defined to capture knowledge in a legal domain and to provide justification and transparency of legal decisions. First, a legal domain ADF is instantiated from the factor hierarchy of CATO and IBP, then the method is applied to the other two legal domains. In each domain, the cases are expressed in terms of factors organised into an ADF, from which an executable program can be implemented in a straightforward way by taking advantage of the closeness of the acceptance conditions of the ADF to components of an executable program. The proposed method is evaluated to test the ease of implementation, the efficacy of the resulting program, the ease of refinement, transparency of the reasoning and transferability across legal domains. This evaluation suggests ways of improving the decision by incorporating the case facts, and considering justification and reasoning using portions of precedents. The final result is ANGELIC (ADF for kNowledGe Encapsulation of Legal Information from Cases), a method for producing programs that decide the cases with a high degree of accuracy in multiple domains