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Chapter and Conference Paper
Explaining Model Behavior with Global Causal Analysis
We present Global Causal Analysis (GCA) for text classification. GCA is a technique for global model-agnostic explainability drawing from well-established observational causal structure learning algorithms. GCA g...
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Article
Correction: thirty years of Artificial Intelligence and Law: the second decade
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Article
Thirty years of Artificial Intelligence and Law: the second decade
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 r...
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Article
Open AccessA formal analysis of some factor- and precedent-based accounts of precedential constraint
In this paper several recent factor- and dimension-based models of precedential constraint are formally investigated and an alternative dimension-based model is proposed. Simple factor- and dimension-based syn...
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Chapter and Conference Paper
Philosophical Reflections on Argument Strength and Gradual Acceptability
This paper proposes a classification of three aspects of argument strength based on philosophical insights, in particular Aristotle’s distinction between logic, dialectic and rhetoric. It is then argued that w...
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Article
Open AccessIn memoriam Douglas N. Walton: the influence of Doug Walton on AI and law
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 wa...
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Article
Open AccessA 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 ...
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Chapter and Conference Paper
Constructing Bayesian Network Graphs from Labeled Arguments
Bayesian networks (BNs) are powerful tools that are well-suited for reasoning about the uncertain consequences that can be inferred from evidence. Domain experts, however, typically do not have the expertise t...
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Chapter
Argument
This chapter discusses how formal models of argumentation can clarify philosophical problems and issues. Some of these arise in the field of epistemology, where it has been argued that the principles by which ...
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Chapter and Conference Paper
Refining a Heuristic for Constructing Bayesian Networks from Structured Arguments
Recently, a heuristic was proposed for constructing Bayesian networks (BNs) from structured arguments. This heuristic helps domain experts who are accustomed to argumentation to transform their reasoning into ...
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Article
Open AccessOn the problem of making autonomous vehicles conform to traffic law
Autonomous vehicles are one of the most spectacular recent developments of Artificial Intelligence. Among the problems that still need to be solved before they can fully autonomously participate in traffic is ...
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Article
Introduction to the special issue on Artificial Intelligence for Justice (AI4J)
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Chapter and Conference Paper
On Relating Abstract and Structured Probabilistic Argumentation: A Case Study
This paper investigates the relations between Timmer et al.’s proposal for explaining Bayesian networks with structured argumentation and abstract models of probabilistic argumentation. First some challenges a...
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Article
Open AccessA method for explaining Bayesian networks for legal evidence with scenarios
In a criminal trial, a judge or jury needs to reason about what happened based on the available evidence, often including statistical evidence. While a probabilistic approach is suitable for analysing the stat...
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Chapter and Conference Paper
Explaining Bayesian Networks Using Argumentation
Qualitative and quantitative systems to deal with uncertainty coexist. Bayesian networks are a well known tool in probabilistic reasoning. For non-statistical experts, however, Bayesian networks may be hard to...
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Chapter
Formalising Debates About Law-Making Proposals as Practical Reasoning
In this paper the ASPIC + framework for argumentation -based inference is used for formally reconstructing two legal debates about law-making proposals: an opinion of a legal scholar on a Dutch legislative propos...
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Article
Building Bayesian networks for legal evidence with narratives: a case study evaluation
In a criminal trial, evidence is used to draw conclusions about what happened concerning a supposed crime. Traditionally, the three main approaches to modeling reasoning with evidence are argumentative, narrat...
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Chapter and Conference Paper
Risk Assessment as an Argumentation Game
This paper explores the idea that IT security risk assessment can be formalized as an argumentation game in which assessors argue about how the system can be attacked by a threat agent and defended by the asse...
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Article
A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law
We provide a retrospective of 25 years of the International Conference on AI and Law, which was first held in 1987. Fifty papers have been selected from the thirteen conferences and each of them is described i...
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Article
Open AccessReconstructing Popov v. Hayashi in a framework for argumentation with structured arguments and Dungean semantics
In this article the argumentation structure of the court’s decision in the Popov v. Hayashi case is formalised in Prakken’s (Argument Comput 1:93–124; 2010) abstract framework for argument-based inference with st...
