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 …

A Bayesian network (BN) is a graphical model of uncertainty that is especially well suited to
legal arguments. It enables us to visualize and model dependencies between different …

This paper proposes a systematized presentation and a terminology for observations in a
Bayesian network. It focuses on the three main concepts of uncertain evidence, namely …

Bayesian networks (BN) and argumentation diagrams (AD) are two predominant
approaches to legal evidential reasoning, that are often treated as alternatives to one …

Abstract Cardiac Implantable Medical devices (IMD) are increasingly being used by patients
to benefit from their therapeutic and life-saving functions. These medical devices are …

Bayesian networks are a predominant approach to analyse the findings of forensic
scientists. In part, this is due to the way the Bayesian approach fits the scientific method …

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 …

Surprisingly, evidence used to be a Cinderella until the late 1990s in 'AI & Law'(artificial
intelligence for law), itself a burgeoning domain already in the 1980s. It was not until the …

Crime investigation is a complex task involving huge amounts of information and requiring
many different types of expert knowledge. To improve policies and develo** effective …

Abstract Argumentation theory is an interdisciplinary field studying how conclusions can be
reached through logical reasoning. The notion of argument is completely general, including …