In this paper we describe the impact that Walton’s conception of argumentation schemes had on AI and Law research. We will discuss developments in argumentation in AI and Law before Walton’s schemes became known in that community, and the issues that were current in that work. We will then show how Walton’s schemes provided a means of addressing all of those issues, and so supplied a unifying perspective from which to view argumentation in AI and Law.

The first issue of Artificial Intelligence and Law journal was published in 1992. This paper provides commentaries on nine significant papers drawn from the Journal’s second decade. Four of the papers relate to reasoning with legal cases, introducing contextual considerations, predicting outcomes on the basis of natural language descriptions of the cases, comparing different ways of representing cases, and formalising precedential reasoning. One introduces a method of analysing arguments that was to become very widely used in AI and Law, namely (...) argumentation schemes. Two relate to ontologies for the representation of legal concepts and two take advantage of the increasing availability of legal corpora in this decade, to automate document summarisation and for the mining of arguments. (shrink)

Plausible (eikotic) reasoning known from ancient Greek (late Academic) skeptical philosophy is shown to be a clear notion that can be analyzed by argumentation methods, and that is important for argumentation studies. It is shown how there is a continuous thread running from the Sophists to the skeptical philosopher Carneades, through remarks of Locke and Bentham on the subject, to recent research in artificial intelligence. Eleven characteristics of plausible reasoning are specified by analyzing key examples of it recognized as important (...) in ancient Greek skeptical philosophy using an artificial intelligence model called the Carneades Argumentation System (CAS). By applying CAS to ancient examples it is shown how plausible reasoning is especially useful for gaining a better understanding of evidential reasoning in law, and argued that it can also be applied to everyday argumentation. Our analysis of the snake and rope example of Carneades is also used to point out some ways CAS needs to be extended if it is to more fully model the views of this ancient philosopher on argumentation. (shrink)

The first issue of _Artificial Intelligence and Law_ journal was published in 1992. This paper provides commentaries on landmark papers from the first decade of that journal. The topics discussed include reasoning with cases, argumentation, normative reasoning, dialogue, representing legal knowledge and neural networks.

In this paper we describe the impact that Walton’s conception of argumentation schemes had on AI and Law research. We will discuss developments in argumentation in AI and Law before Walton’s schemes became known in that community, and the issues that were current in that work. We will then show how Walton’s schemes provided a means of addressing all of those issues, and so supplied a unifying perspective from which to view argumentation in AI and Law.

This paper has three dimensions, historical, theoretical and social. The historical dimension is to show how the Ciceronian system of dialectical argumentation served as a precursor to computational models of argumentation schemes such as Araucaria and Carneades. The theoretical dimension is to show concretely how these argumentation schemes reveal the interdependency of rhetoric and logic, and so the interdependency of the normative with the empirical. It does this by identifying points of disagreement in a dialectical format through using argumentation schemes (...) and critical questions. The social dimension is to show how the Ciceronian dialectical viewpoint integrates with the use of computational tools that can be used to support the principle of reason-based deliberation and facilitate deliberative democracy. (shrink)

Doug Walton, who died in January 2020, was a prolific author whose work in informal logic and argumentation had a profound influence on Artificial Intelligence, including Artificial Intelligence and Law. He was also very interested in interdisciplinary work, and a frequent and generous collaborator. In this paper seven leading researchers in AI and Law, all past programme chairs of the International Conference on AI and Law who have worked with him, describe his influence on their work.

This paper applies two argumentation schemes, argument from fairness and argument from lack of knowledge (along with other schemes of lesser prominence) to model the reasoning given by Judge McCarthy supporting his decision to divide the proceeds of a homerun baseball in the case of Popov v. Hayashi. Several versions of both schemes are explained and discussed, and then applied to the argumentation given by Judge McCarthy as the basis of the reasoning used to arrive at his decision. The scheme (...) for argument from fairness is shown to be based on a special principle in Perelman’s theory of justice. (shrink)