ABSTRACT Reverse eikos (plausibility) arguments are notorious for reversing a reason that supports an accusation into a reason that denies this accusation. This article offers new insights on their analysis and evaluation, by reconstructing a reverse eikos argument’s line of reasoning as an argumentative pattern. The pattern reveals that this type of argument centers not only on the arguer’s claim that by doing the act of which they have been accused, they would risk becoming the likely suspect, but also on (...) the connected reasoning that they would not want to risk this since that would be stupid and they are not stupid. The proposed analysis, which is illustrated with classic and modern examples of reverse eikos arguments, shows that the evaluation of these arguments boils down to estimating the arguer’s calculation of the costs and benefits of taking the risk, while taking into account the arguer’s character, intellect, and circumstances. (shrink)

According to the argument scheme approach, to evaluate a given scheme-saturating instance completely does entail asking all critical questions relevant to it. Although this is a central task for argumentation theorists, the field currently lacks a method for providing a complete argument evaluation. Approaching this task at the meta-level, we combine a logical with a substantive approach to the argument schemes by starting from Toulmin’s schema: ‘data, warrant, so claim’. For the yet more general schema: ‘premise; if premise, then conclusion; (...) so conclusion’, we forward a meta-level CQ-list that is arguably both complete and applicable. This list should inform ongoing theoretical efforts at generating appropriate object-level CQs for specific argument schemes. (shrink)

This article presents an analysis and evaluation of what I call the “I’m not stupid” argument. This argument has ancient roots, which lie in Aristotle’s famous description of the weak man’s and strong man’s arguments. An “I’m not stupid” argument is typically used in a context of accusation and defense, by a defendant who argues that they did not commit the act of which they have been accused. The analysis of this type of argument takes the shape of an argumentative (...) pattern, which displays a full-fledged representation of its argumentation structure. It is based on a collection of ten contemporary instances of the “I’m not stupid” argument. Although ten instances constitute a small collection, the wide variation in the argumentative elements that they express explicitly or leave implicit made it possible to identify five new key premises in comparison with previous analyses of the weak man’s and strong man’s arguments (Walton, Tindale and Gordon 2014 in _Argumentation_ 28:85–119, 2014; Walton 2019 in _Argumentation_ 33:45–74, 2019). These new premises show that the crucial point of an evaluation of this argument is the arguer's supposedly rational character in making a gain-loss calculation. They also show that we need empirical data to strengthen our analyses of argument schemes and argumentation structures. (shrink)

In this paper it is shown how plausible reasoning of the kind illustrated in the ancient Greek example of the weak and strong man can be analyzed and evaluated using a procedure in which the pro evidence is weighed against the con evidence using formal, computational argumentation tools. It is shown by means of this famous example how plausible reasoning is based on an audience’s recognition of situations of a type they are familiar with as normal and comprehensible in their (...) shared common knowledge. The paper extends previous work on this example by using three new multiagent argumentation schemes closely related to the scheme for argument from negative consequences. (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.

Belief formation and justification of belief is the subject of epistemology, philosophy of mind, and philosophy of action. In this article we are mostly interested in the application of analytic techniques for the explication of belief justification under uncertainty. We need to explicate this phenomenon in order to answer, at least in part, the question of what are the features of reasoning made in conditions that cause doubts, how people make decisions in such conditions. Arguments used for the justification of (...) such decisions have the status of plausible arguments. The crucial issues related to the analysis and evaluation of plausible arguments are of the acceptability of the premises and the transmission of their acceptability to the conclusion. In this article, we have focused on the transition from the premises to the conclusions of plausible arguments, on the transmission of justification of premises to the conclusions. To establish the peculiarities of such a transmission an outline of the semantics for such arguments is proposed. Its key component is the measures of the plausibility of the premises and rules of inference. A plausible argument itself does not provide the ultimate reason for accepting its conclusion. The justification of the conclusion also depends on other arguments that support or defeat it. So to establish the degree of justification of the conclusion we need to attribute the weights to the premises and rules of inference. We hope that this study provides at least a preliminary answer to the question of how the failure of the transmission of justification in plausible arguments differs from the failure of transmission in deductive arguments. (shrink)

Even though tools for identifying and analyzing arguments are now in wide use in the field of argumentation studies, so far there is a paucity of resources for evaluating real arguments, aside from using deductive logic or Bayesian rules that apply to inductive arguments. In this paper it is shown that recent developments in artificial intelligence in the area of computational systems for modeling defeasible argumentation reveal a different approach that is currently making interesting progress. It is shown how these (...) systems provide the general outlines for a system of argument evaluation that can be applied to legal arguments as well as everyday conversational arguments to assist a user to evaluate an argument. (shrink)

This essay addresses the collapse/incoherence problem for normative frameworks that contain both fundamental values and rules for promoting those values. The problem is that in some cases, we would bring about more of the fundamental value by violating the framework’s rules than by following them. In such cases, if the framework requires us to follow the rules anyway, then it appears to be incoherent; but if it allows us to make exceptions to the rules, then the framework “collapses” into one (...) that doesn’t make use of rules in the first place. The chapter begins with an examination of happiness and truth as fundamental values in Mill’s work, which lead into parallel versions of the collapse/incoherence problem in ethics and epistemology. It then sets out the collapse problem for rule-consequentialist approaches in ethics, truth-directed accounts of justification in epistemology, and epistemological approaches to argument cogency. The chapter closes with discussion of two potential solutions to the problem. (shrink)