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.

In this paper, we continue our research on a hybrid narrative-argumentative approach to evidential reasoning in the law by showing the interaction between factual reasoning (providing a proof for ‘what happened’ in a case) and legal reasoning (making a decision based on the proof). First we extend the hybrid theory by making the connection with reasoning towards legal consequences. We then emphasise the role of legal stories (as opposed to the factual stories of the hybrid theory). Legal stories provide a (...) coherent, holistic legal perspective on a case. They steer what needs to be proven but are also selected on the basis of what can be proven. We show how these legal stories can be used to model a shift of the legal perspective on a case, and we discuss how gaps in a legal story can be filled using a factual story (i.e. the process of reasoning with circumstantial evidence). Our model is illustrated by a discussion of the Dutch Wamel murder case. (shrink)

In 2018, three journalists accused one of the Members of the Russian Parliament of harassment at workplace. Many influential persons of the Russian elite engaged themselves in the public discussion of the conflict. We studied that high-profiled discussion using a hybrid method merging human- and logic-oriented approaches in argumentation studies. The method develops ideas of the new dialectics, the argumentation logic and the logical-cognitive approach to argumentation, on which is based the algorithm for determining of dispute resolution by aggregating formal (...) and informal tools of analysis. We have reconstructed the discussion as two disputes about questions A and B. A: Did the MP violate the code of conduct by making statements or actions against the journalists? B: Are actions like the behavior of the MP harassment? The opinions of the discussion participants were grouped into the four points of view: A1 – the MP did not violate the code of conduct, A2 – the MP violated the code of conduct, B3 – the actions are not harassment, B4 – the actions are harassment. We mapped arguments in support or against each of them using OVA software, evaluated the arguments with the help of the critical questions, a tool proposed in the new dialectics, and determined the ultimate A + B resolution by applying of the algorithm that combines elements of gradual and labelling semantics from the argumentation logic and the classification of disputes from the dialectical approaches. The resolution was a subset of four arguments that ensured the victory of A1+B4. However, the substantial incompatibility of those arguments highlighted a deep disagreement, an unresolvable difference of opinion, between the parties about the permissibility of courtship. The deep disagreement, a bonus result yielded by the application of the hybrid method, excluded the interpretation of the determined resolution as convincing for the parties, but pointed out a way to smooth the difference of opinions by elaborating of legal, social and moral aspects of the problem of harassment at workplace. (shrink)

Information technology is so ubiquitous and AI’s progress so inspiring that also legal professionals experience its benefits and have high expectations. At the same time, the powers of AI have been rising so strongly that it is no longer obvious that AI applications (whether in the law or elsewhere) help promoting a good society; in fact they are sometimes harmful. Hence many argue that safeguards are needed for AI to be trustworthy, social, responsible, humane, ethical. In short: AI should be (...) good for us. But how to establish proper safeguards for AI? One strong answer readily available is: consider the problems and solutions studied in AI & Law. AI & Law has worked on the design of social, explainable, responsible AI aligned with human values for decades already, AI & Law addresses the hardest problems across the breadth of AI (in reasoning, knowledge, learning and language), and AI & Law inspires new solutions (argumentation, schemes and norms, rules and cases, interpretation). It is argued that the study of AI as Law supports the development of an AI that is good for us, making AI & Law more relevant than ever. (shrink)

Bex analyzes the case with an informal version of his hybrid theory, which combines scenario construction and argumentation. Arguments based on evidence can be used to reason about alternative scenarios. Bex claims that his hybrid theory provides the best of both worlds by combining cognitively feasible story‐based reasoning with more detailed rational argumentation. However, like the argument‐based approach, the hybrid theory does not provide a systematic account of uncertainty.

When the likelihood ratio approach is employed for evidential reasoning in law, it is often necessary to employ subjective probabilities, which are probabilities derived from the opinions and judgement of a human. At least three concerns arise from the use of subjective probabilities in legal applications. Firstly, human beliefs concerning probabilities can be vague, ambiguous and inaccurate. Secondly, the impact of this vagueness, ambiguity and inaccuracy on the outcome of a probabilistic analysis is not necessarily fully understood. Thirdly, the provenance (...) of subjective probabilities and the associated potential sources of vagueness, ambiguity and inaccuracy tend to be poorly understood, making it difficult for the outcome of probabilistic reasoning to be explained and validated, which is crucial in legal applications. The former two concerns have been addressed by a wide body of research in AI. The latter, however, has received little attention. This paper presents a novel approach to employ argumentation to reason about probability distributions in probabilistic models. It introduces a range of argumentation schemes and corresponding sets of critical questions for the construction and validation of argument models that define sets of probability distributions. By means of an extended example, the paper demonstrates how the approach, argumentation schemes and critical questions can be employed for the development of models and their validation in legal applications of the likelihood ratio approach to evidential reasoning. (shrink)

TED Talks are still an unexplored genre of argumentation in which narrative arguments are often used in TED speakers’ strategic maneuvering to support a standpoint. In the present study, I combine the constructs of narrative positioning (NP) and strategic maneuvering (SM) to offer a conceptualization of how narrative is used in pragmatic argumentation as well as provide an exemplary analysis of a specific case of narrative arguments that were used in Winch’s (How to practice emotional first aid. https://www.ted.com/talks/guy_winch_the_case_for_emotional_hygiene.2014, 2014) TED (...) Talk. The proposed integration aims to provide a theoretical framework and empirical tools for reconstructing narrative arguments through connecting the underlying formal structure of narrative with aspects of TED speakers’ strategic maneuvering. Drawing on NP and SM constructs, the critical analysis explores how Winch’s narratives or “small stories” were strategically manipulated to support his stance with regard to the importance of mental health and to examine whether or not the use of narrative arguments as argumentation moves helped to enhance the dialectical reasonableness and rhetorical effectiveness of Winch’s argument. The analysis shows that the macro context and the knowledge gap between TED speakers and the audience makes the use of narrative arguments extremely effective. Although narrative arguments often receive criticism about their validity in providing sufficient evidence for a standpoint, their dialectical power lies in the flexibility of describing events in different fashions to draw pragmatic inferences that support the speaker’s stance. The study fills an important gap in the literature as it integrates recent approaches in narrative theory in the reconstruction and evaluation of narrative arguments in TED Talks. (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)

Whether abduction is treated as an argument or as an inference, the mainstream view presupposes a tight connection between abduction and inference to the best explanation. This paper critically evaluates this link and supports a narrower view on abduction. Our main thesis is that merely the hypothesis-generative aspect, but not the evaluative aspect, is properly abductive in the sense introduced by C. S. Peirce. We show why equating abduction with IBE unnecessarily complicates argument evaluation by levelling the status of abduction (...) as a third reasoning mode. We also propose a scheme for abductive argument along with critical questions, and suggest retaining abduction alongside IBE as related but distinct categories. (shrink)