The purpose of this paper is to analyze the structure and the defeasibility conditions of argument from analogy, addressing the issues of determining the nature of the comparison underlying the analogy and the types of inferences justifying the conclusion. In the dialectical tradition, different forms of similarity were distinguished and related to the possible inferences that can be drawn from them. The kinds of similarity can be divided into four categories, depending on whether they represent fundamental semantic features of the (...) terms of the comparison or non-semantic ones, indicating possible characteristics of the referents. Such distinct types of similarity characterize different kinds of analogical arguments, all based on a similar general structure, in which a common genus is abstracted. Depending on the nature of the abstracted common feature, different rules of inference will apply, guaranteeing the attribution of the analogical predicate to the genus and to the primary subject. This analysis of similarity and the relationship thereof with the rules of inference allows a deeper investigation of the defeasibility conditions. (shrink)

In this paper a hybrid model of argument from analogy is presented that combines argumentation schemes and story schemes. One premise of the argumentation scheme for argument from analogy in the model claims that one case is similar to another. Story schemes are abstract representations of stories (narratives, explanations) based on common knowledge about how sequences of actions and events we are familiar with can normally be expected to unfold. Story schemes are used (a) to model similarity between two cases, (...) and (2) as the basis of evidence to support the similarity premise of an argument from analogy. Four examples of argument from analogy are used to test the theory. (shrink)

We present a high-level declarative programming language for representing argumentation schemes, where schemes represented in this language can be easily validated by domain experts, including developers of argumentation schemes in informal logic and philosophy, and serve as executable specifications for automatically constructing arguments, when applied to a set of assumptions. This new rule language for representing argumentation schemes is validated by using it to represent twenty representative argumentation schemes.

The first issue of _Artificial Intelligence and Law_ journal was published in 1992. This paper discusses several topics that relate more naturally to groups of papers than a single paper published in the journal: ontologies, reasoning about evidence, the various contributions of Douglas Walton, and the practical application of the techniques of AI and Law.

Arguers sometimes cite a decision made in an earlier situation as a reason for making the equivalent decision in a later situation. I argue that there are two kinds of “case-to-case arguments”. First, there are arguments by precedent, which cite the mere existence of the past decision as a reason to decide in the same way again now, independent of the past decision’s merits. Second, there are case-to-case arguments from parralel reasoning which presuppose that the past decision was justified and (...) are used to show that an equivalent present decision would also be justified. Both arguments are a type of argument by analogy. They differ in their structures and conditions of cogency, even though they often look the same in presentation. Their similar appearance poses a risk of miss-evaluation and fallacious use. Therefore a clearly theorized distinction is important. (shrink)

This chapter proposes a dialectical approach to legal interpretation, consisting of three dimensions: a formalization of the canons of interpretation in terms of argumentation schemes; a dialectical classification of interpretive schemes; and a logical and computational model for comparing the arguments pro and contra an interpretation. The traditional interpretive maxims or canons used in both common and civil law are translated into defeasible patterns of arguments, which can be evaluated through sets of corresponding critical questions. These interpretive argumentation schemes are (...) classified in general categories and a distinction is drawn between schemes supporting and rebutting an interpretation. This framework allows conceiving statutory interpretation as a dialectical procedure consisting in weighing arguments pro and contra an interpretation. This procedure is formalized and represented computationally through tools from formal argumentation systems. (shrink)

This paper applies recent work on scripts and stories developed as tools of evidential reasoning in artificial intelligence to model the use of argument from analogy as a rhetorical device of persuasion. The example studied is Gerry Spence’s closing argument in the case of Silkwood v. Kerr-McGee Corporation, said to be the most persuasive closing argument ever used in an American trial. It is shown using this example how argument from analogy is based on a similarity premise where similarity between (...) two cases is modeled using the device of a story scheme from the hybrid theory of legal evidential reasoning (Bex in Arguments, stories and criminal evidence: a formal hybrid theory. Springer, Dordrecht 2011). It is shown how the rhetorical strategy of Spence’s argumentation in the closing argument interweaves argument from analogy with explanation through three levels. (shrink)

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. (shrink)

Abstract. The notion of similarity has been studied in many areas of Computer Science; in a general sense, this concept is defined to provide a measure of the semantic equivalence between two pieces of knowledge, expressing how “close” their meaning can be regarded. In this work, we study similarity as a tool useful to improve the representation of arguments, the interpretation of the relations between arguments, and the semantic evaluation associated with the arguments in the argumentative process. In this direction, (...) we present a novel mechanism to determine the similarity between two arguments based on descriptors representing particular aspects associated with these arguments. This mechanism involves a comparison process influenced by the context in which the process develops, where this context provides the relevant aspects that need to be analyzed in the application domain. Then, we use this similarity measure as a quantity to compute the result of attacks and supports in the argumentation process. These valuations, applied to a Bipolar Argumentation Frameworks, allowed us to refine the argument relations, providing the tools to establish a family of new argumentation semantics that considers the similarity between arguments as a crucial part for the argumentation process. (shrink)

We present a high-level declarative programming language for representing argumentation schemes, where schemes represented in this language can be easily validated by domain experts, including developers of argumentation schemes in informal logic and philosophy, and serve as executable specifications for automatically constructing arguments, when applied to a set of assumptions. Since argumentation schemes are defeasible inference rules, both premises and conclusions of schemes can be second-order schema variables, i.e. without a fixed predicate symbol. Thus, while particular schemes can be and (...) have been implemented in computer programs, in general argumentation schemes cannot be represented as executable specifications using logic programming languages based on first-order logic, such as Prolog. Moreover, even if the conclusion (head) of Prolog rules could be second-order variables, a depth-first, backward-chaining search strategy, as typically used in logic programming, would usually cause such programs to not terminate, since every goal would match the head of such a scheme, including all goals created by instantiating the body of the same scheme. The language for representing argumentation schemes presented here, for the purpose of automatically constructing arguments, uses Constraint Handling Rules (CHR), a declarative, Turing complete, forwards-chaining, rule-based programming language introduced by Thom Frühwirth in 1991. CHR is attractive for representing and implementing argumentation for several reasons, including: 1) Inference rules, rewrite rules, sequents, proof rules, and logical axioms can be directly written in CHR. 2) The execution of CHR rules can be interrupted and restarted at any time, with intermediate results approximating the final solution, and 3) Constraints can be input incrementally as they become known, during rule execution, without requiring recomputation. These three properties of CHR appear attractive for representing and implementing argumentation schemes. Since argumentation schemes are (defeasible) inference rules, the ability of CHR to represent inference rules directly would appear to be quite useful. The ability to stop the computation and produce approximate results is compatible with one objective of argumentation, to provide a principled method for supporting approximate reasoning with limited resources. Because argumentation typically takes place in dialogs, with evidence and arguments brought forward and asserted by the participants incrementally, during the course of the dialog, CHR’s ability to handle new information, incrementally introduced during the computation, may be useful. This new rule language for representing argumentation schemes is validated by using it to represent twenty representative argumentation schemes. (shrink)

The notion of similarity has been studied in many areas of Computer Science; in a general sense, this concept is defined to provide a measure of the semantic equivalence between two pieces of knowledge, expressing how “close” their meaning can be regarded. In this work, we study similarity as a tool useful to improve the representation of arguments, the interpretation of the relations between arguments, and the semantic evaluation associated with the arguments in the argumentative process. In this direction, we (...) present a novel mechanism to determine the similarity between two arguments based on descriptors representing particular aspects associated with these arguments. This mechanism involves a comparison process influenced by the context in which the process develops, where this context provides the relevant aspects that need to be analyzed in the application domain. Then, we use this similarity measure as a quantity to compute the result of attacks and supports in the argumentation process. These valuations, applied to a Bipolar Argumentation Frameworks, allowed us to refine the argument relations, providing the tools to establish a family of new argumentation semantics that considers the similarity between arguments as a crucial part for the argumentation process. (shrink)

I will demonstrate that conductive arguments are found in the inference to the best explana-tion as it is used in science. Conductive arguments, I argue, operate on two levels: the first is in the con-struction of hypotheses; the second is through the competition of hypotheses. By constructing arguments based on observations of facts, all possible factors are taken into account and a judgment is made based on our weighing of considerations: conductive argumentation.

Analogical reasoning projects a property taken to hold of something or things (the source) to something else (the target) on the basis of just those similarities premised in the analogy. Standard similarity-based accounts of analogical reasoning face the question: Under what conditions does a collection of similarities sufficiently warrant analogical projection? One answer is: When a thing’s having the premised similarities somehow determines its having the projected property. Standardly, this answer has been interpreted as claiming that a formally defined determination (...) relation exists between the variables of which the determining properties are values and the variable of which the determined property is a value. This paper supplies another answer: Analogical projection is warranted when an item’s having the projected property is grounded in its having the premised similarities. Drawing on the metaphysics of grounding, we propose a model of grounded analogy on which analogical reasoning is valid under metaphysical necessity. Our model thus provides one answer to John Stuart Mill’s question of how analogical reasoning based on limited information about a single source case can provide an indefeasible justification for analogical projection. Once a relation of total grounding is ascertained to hold between some similarities and the projected property, no other properties bear on the projectability of the projected property from the source to the target. (shrink)

We present a novel argumentation-based method for finding and analyzing communities in social media on the Web, where a community is regarded as a set of supported opinions that might be in conflict. Based on their stance, we identify argumentative coalitions to define them; then, we apply a similarity-based evaluation method over the set of arguments in the coalition to determine the level of cohesion inherent to each community, classifying them appropriately. Introducing conflict points and attacks between coalitions based on (...) argumentative (dis)similarities to model the interaction between communities leads to considering a meta-argumentation framework where the set of coalitions plays the role of the set of arguments and where the attack relation between the coalitions is assigned a particular strength which is inherited from the arguments belonging to the coalition. Various semantics are introduced to consider attacks’ strength to particularize the effect of the new perspective. Finally, we analyze a case study where all the elements of the formal construction of the formalism are exercised. (shrink)

The passage of time influences the content of the law and therefore also the validity of legal arguments. This is true even for charter-arguments, despite the widely held view that constitutional law is made to last. In this paper, I investigate the reason why the sanctity-of life argument against physician assisted suicide lost its validity between the Supreme Court decision in Rodriguez v. British Columbia in 1993 and Carter v. Canada in 2015. I suggest that a rhetorical approach to argument (...) evaluation is the best basis for a satisfying explanation. (shrink)

This paper explores the question of whether or not the law is a computable number in the sense described by Alan Turing in his 1937 paper ‘On computable numbers with an application to the Entscheidungsproblem.’ Drawing upon the legal, social, and political context of Alan Turing’s own involvement with the law following his arrest in 1952 for the criminal offence of gross indecency, the article explores the parameters of computability within the law and analyses the applicability of Turing’s computability thesis (...) within the context of legal decision-making. (shrink)

At a recent rally, Donald Trump resumed a habit he had developed during his election-rallies and read out the lyrics to a song. It tells the Aesopian fable of The Farmer and the Snake: A half frozen snake is taken in by a kind-hearted person but bites them the moment it is revived. Trump tells the fable to make a point about Islamic immigrants and undocumented immigrants from Southern and Central America: He claims the immigrants will cause problems and much (...) stricter immigration-policies are needed. I assume that Trump treats the fable as an argumentative device for supporting his stance on immigration. He uses it as a source-analogue both for the conclusion that immigrants will cause problems and for changing the frame in which immigrants and those willing to let them enter are seen. This gives me opportunity to examine the effect fables have as argumentative devices. Fables are a popular and effective choice for political argumentation. They are slimmed down, semi-abstract narratives, well suited for directing the audience's attention to a few properties of an otherwise complex situation. However, this also makes it easy to use them for manipulating an audience into oversimplifying complex contexts and stereotyping human beings. (shrink)

The Toulmin model has been proved useful in law and argumentation theory. This model describes the basic process in justifying a claim, which comprises six elements, i.e., claim (C), data (D), warrant (W), backing (B), qualifier (Q), and rebuttal (R). Specifically, in justifying a claim, one must put forward ‘data’ and a ‘warrant’, whereas the latter is authorized by ‘backing’. The force of the ‘claim’ being justified is represented by the ‘qualifier’, and the condition under which the claim cannot be (...) justified is represented as the ‘rebuttal’. To further improve the model, (Goodnight, Informal Logic 15:41–52, 1993) points out that the selection of a backing needs justification, which he calls legitimation justification. However, how such justification is constituted has not yet been clarified. To identify legitimation justification, we separate it into two parts. One justifies a backing’s eligibility (legitimation justification 1 ; LJ 1 ); the other justifies its superiority over other eligible backings (legitimation justification 2 ; LJ 2 ). In this paper, we focus on LJ 1 and apply it to the legal justification (of judgements) in hard cases for illustration purposes. We submit that LJ 1 refers to the justification of the legal interpretation of a norm by its backing, which can be further separated into several orderable subjustifications. Taking the subjustification of a norm’s existence as an example, we show how it would be influenced by different positions in the philosophy of law. Taking the position of the theory of natural law, such subjustification is presented and evaluated. This paper aims not only to inform ongoing theoretical efforts to apply the Toulmin model in the legal field, but it also seeks to clarify the process in the justification of legal judgments in hard cases. It also offers background information for the possible construction of related AI systems. In our future work, LJ 2 and other subjustifications of LJ 1 will be discussed. (shrink)

The concept of conductive argument weight was developed by Carl Wellman and later by Trudy Govier. This concept has received renewed attention recently from another informal logician, Robert C. Pinto. Argument weight has also been addressed in recent years by theorists in AI & Law. I argue from a non-technical perspective that some aspects of AI & Law’s approach to argument weight can be usefully applied to the issues addressed by Pinto. I also relate some of these issues to the (...) work of argument theorist Harald Wohlrapp. (shrink)