Legal analogical reasoning - the interplay between legal theory and artificial intelligence

This thesis examines and critiques attempts by researchers in the field of artificial intelligence and law to simulate legal analogical reasoning. Supported by an analysis of legal theoretical accounts of legal analogising, and an examination of approaches to simulating analogising developed in the field of artificial intelligence, it is argued that simulations of legal analogising fall far short of simulating all the is involved in human analogising. These examinations of legal theory and artificial intelligence inform a detailed critique of simulations of legal analogising. It is argued that simulations of legal analogising are limited in the kind of legal analogising they can simulate - these simulations cannot simulate the semantic flexibility that is characteristic of creative analogising. This thesis argues that one reason for current restrictions on simulations of legal analogising is that researchers in artificial intelligence and law have ignored the important role played by legal principles in legal analogising. It is argued that improvements in simulations of legal analogising will come from incorporating the influence of legal principles on legal analogising and that until researchers address this semantic flexibility and the role that legal principles play in generating it, simulations of legal analogising will be restricted and of benefit only for limited uses and in restricted areas of the law. Building on the analysis of legal theoretical accounts of legal reasoning and the examination of the processes of analogising, this thesis further argues that legal theoretical accounts of legal analogising are insufficient to account for legal analogising. This thesis argues that legal theorists have themselves ignored important aspects of legal analogising and hence that legal theoretical accounts of legal analogising are deficient. This thesis offers suggestions as to some of the modifications required in legal theory in order to better account for the processes of legal analogising

Review of \u27Artificial Legal Intelligence\u27

Artificial Legal Intelligence, by Pamela Gray, presents a thought-provoking approach to both computational models of legal reasoning and the use of evolutionary thinking about the law. Drawing on a prodigious amount of research, the book looks beyond the rather technical approach common in the field and attempts to place artificial legal intelligence within the broad structure of legal history. This paper first summarizes the book\u27s vision of a computerized artificial legal intelligence, a vision of developments in both technology and legal history. The paper discusses how this fits with trends in both artificial intelligence and legal theory. The paper further discusses how the book, by freeing itself from present technological constraints, provides a wider vision than many more technical discussions of artificial intelligence. In particular, its view of the evolution of law brings in social and cultural factors often ignored by discussions of legal reasoning. The last part of this paper considers, more broadly, how evolutionary analysis can provide a fruitful method for analyzing legal reasoning

A new use case for argumentation support tools:supporting discussions of Bayesian analyses of complex criminal cases

In this paper a new use case for legal argumentation support tools is considered: supporting discussions about analyses of complex criminal cases with the help of Bayesian probability theory. By way of a case study, two actual discussions between experts in court cases are analysed on their argumentation structure. In this study the usefulness of several recognised argument schemes is confirmed, a new argument scheme for arguments from statistics are proposed, and an analysis is given of debates between experts about the validity of their arguments. From a practical point of view the case study yields insights into the design of support software for discussions about Bayesian analyses of complex criminal cases

How much of commonsense and legal reasoning is formalizable? A review of conceptual obstacles

Fifty years of effort in artificial intelligence (AI) and the formalization of legal reasoning have produced both successes and failures. Considerable success in organizing and displaying evidence and its interrelationships has been accompanied by failure to achieve the original ambition of AI as applied to law: fully automated legal decision-making. The obstacles to formalizing legal reasoning have proved to be the same ones that make the formalization of commonsense reasoning so difficult, and are most evident where legal reasoning has to meld with the vast web of ordinary human knowledge of the world. Underlying many of the problems is the mismatch between the discreteness of symbol manipulation and the continuous nature of imprecise natural language, of degrees of similarity and analogy, and of probabilities

Arguement in the humanities: A knowledge based approach

In this thesis I have a threefold purpose. I will attempt: (a) to present a generic design for a tool - the Argument Support Program - which can be of use in supporting the reasoning of archaeologists (and others especially, but not exclusively, in the humanities); (b) I will present a model of argumentation and debate as the theoretical orientation within which the model is developed; and, (c) I will suggest that this approach is a natural development of several strands of research within the artificial intelligence community. A tripartite model of argument is presented in terms of arguers, the argument structure produced and the argument domain or field. This model subsumes reasoning, interpretation and argument exchange or debate. It is maintained, further, that while this model is generally applicable, specific domains have particular styles of argument. The notion of argument style is discussed in terms of the types of reasoning used. The related concept of relevance in argument is discussed in terms of the specific tokens of these types which may be used in a particular argument. It is argued that archaeology is characterized, at least in part, by the use of argument by analogy and argument from theoretical principles or models. A design for a generic program - the Argument Support Program (ASP) - based on the theoretical principles is delineated. Details of the partial implementation of the model as a constrained debater in the domain of archaeology (ASP for archaeology or ASParch) are presented. Example runs which illustrate how the characterizing features of archaeology are dealt with are also presented as are examples of the various domain and system knowledge bases needed. The application of ASPs to other domains and areas such as literary criticism, legal reasoning and Darwinian theory is discussed. In the final chapter, the achievements and inadequacies of this research are summarized, possible reasons are presented for the inadequacies in the resulting system and future directions discussed

Authority in the common law

Copyright @ 2011 The Author.No abstract available

The Effectiveness of Case-Based Reasoning: An Application in Sales Promotions

This paper deals with Case-based Reasoning (CBR) as a support technology for sales promotion (SP) decisions. CBR-systems try to mimic analogical reasoning, a form of human reasoning that is likely to occur in weakly-structured problem solving, such as the design of sales promotions. In an empirical study, we find evidence that use of the CBR-system improves the quality of SP-campaign proposals. In terms of the creativity of the proposals, decision-makers who think highly divergent (i.e., who tend to generate many, and diverse ideas in response to a problem) benefit most from prolonged system usage. Creativity, in turn, is positively related to the (practical) usability of a proposal. These results suggest that the CBR-system is most effective when it is used as an idea-generation tool that reinforces the strength of divergent (creative) thinkers. A convergent thinking style, in which case the CBR-system has a compensating role, even has a negative impact on CBR-system usage. Increasing the decision-maker's personal belief in the usefulness of the system, e.g., by training or education, may help to alleviate this reluctance to use the CBR-system.marketing management support systems;sales promotions;case-based reasoning;weakly-structured decision making

Legal knowledge-based systems: new directions in system design

This thesis examines and critiques the concept of 'legal knowledge-based’ systems. Work on legal knowledge-based systems is dominated by work in 'artificial intelligence and law’. It seeks to automate the application of law and to automate the solution of legal problems. Automation however, has proved elusive. In contrast to such automation, this thesis proposes the creation of legal knowledge-based systems based on the concept of augmentation of legal work. Focusing on systems that augment legal work opens new possibilities for system creation and use. To inform how systems might augment legal work, this thesis examines philosophy, psychology and legal theory for information they provide on how processes of legal reasoning operate. It is argued that, in contrast to conceptions of law adopted in artificial intelligence and law, 'sensemaking' provides a useful perspective with which to create systems. It is argued that visualisation, and particularly diagrams, are an important and under considered element of reasoning and that producing systems that support diagramming of processes of legal reasoning would provide useful support for legal work. This thesis reviews techniques for diagramming aspects of sensemaking. In particular this thesis examines standard methods for diagramming arguments and methods for diagramming reasoning. These techniques are applied in the diagramming of legal judgments. A review is conducted of systems that have been constructed to support the construction of diagrams of argument and reasoning. Drawing upon these examinations, this thesis highlights the necessity of appropriate representations for supporting reasoning. The literature examining diagramming for reasoning support provides little discussion of appropriate representations. This thesis examines theories of representation for insight they can provide into the design of appropriate representations. It is concluded that while the theories of representation that are examined do not determine what amounts to a good representation, guidelines for the design and choice of representations can be distilled. These guidelines cannot map the class of legal knowledge-based systems that augment legal sensemaking, they can however, be used to explore this class and to inform construction of systems