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Prevention through Design has been identified as an effective means to enhance construction safety. However, design professionals, clients and other stakeholders often have limited experience of construction processes. Although processes and tools have been advanced to support stakeholders, very few have been adopted in practice. The complexities inherent in designing for safe construction suggest this to be a wicked problem using criteria advanced by Rittel and Weber. Approaches advanced to solve wicked problems outside construction are not applicable for solving construction design problems, largely because they require that stakeholders expend an impractical amount of time and energy to arrive at amenable solutions. Instead, an approach that utilises information visualisation addresses criteria for wicked problem resolution. The promise of information visualisation for this wicked problem has been illustrated through a case study involving façade design. An infographic was generated following structured interviews with building designers and safety experts. A workshop involving 20 designers, engineers and safety experts demonstrated that the infographic prompted participants to identify risks not previously considered and stimulated discussion about mitigation or reduction. There was unanimous agreement that the information visualisation could feasibly be adopted within the construction industry’s tight time and resource constraints. [ABSTRACT FROM PUBLISHER]

This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a narrative model that is guided partially by inference and contextual information contained in the particular knowledge representation used, the generic/actual argument model of structured reasoning. The approach is described with examples in the area of critical care nursing training. A study of the effectiveness of this approach on learning outcomes was conducted with final year nursing students and provides evidence of improved learning outcomes. [ABSTRACT FROM AUTHOR]

This article describes an argumentation shell to support the formulation, representation and drafting of legal arguments. The shell can be used to capture generic arguments in many legal domains as well as to assist decision-makers in constructing their own actual arguments. The shell demonstrates that knowledge represented using the generic/actual argument model (GAAM) (a variant of Toulmin's argument structure) can be used to: (a) support the development of complex arguments, (b) add context and increase specificity for the retrieval of relevant documents, (c) incorporate background knowledge, (d) assist in the drafting of documents that represent arguments made, and (e) provide a structure for complex inferences requiring a range of mechanisms. The shell can be used to support decision making in a range of legal domains, including discretionary domains. [ABSTRACT FROM AUTHOR]

Knowledge-based systems can make a contribution to the difficult problem of regulating copyright on the internet. Regulation with law alone presents significant jurisdictional and enforcement difficulties whereas regulation with the use of encryption has the effect of removing legitimate public access to works for research, private study or criticism. Knowledge-based systems proposed here operate at five junctures: creating works, uploading works to a network, transmitting the work across the internet, downloading a work and using the creation. For each system, we apply an agent-based architecture that defines the actors, the knowledge all agents share about the world and a protocol, based on Habermasian speech acts to interact with other agents. The shared knowledge, and beliefs about the world, that each agent holds is represented with the use of arguments at two levels, the generic and the actual argument level. This application of argumentation extends our previous work in family law and refugee law. [ABSTRACT FROM AUTHOR]

Argues that discretion manifests differently in different representations of knowledge. Discretion in legal theory; First-order logic formalization; Association between discretion and a Toulmin representation of reasoning; Analysis of consistency.

An Electronic Health Record (EHR) is an individual's record of all health events that enables critical information to be documented and shared electronically amongst health care providers and patients. The introduction of an EHR, particularly a patient-accessible EHR, can be expected to lead to an escalation of enquiries, complaints and ultimately, disputes. Prevailing opinion is that Online Dispute Resolution (ODR) systems can help with the mediation of certain types of disputes electronically, particularly systems which deploy Artificial Intelligence (AI) to reduce the need for a human mediator. However, disputes regarding health tend to invoke emotional responses from patients that may conceivably impact ODR efficacy. This raises an interesting question on the influence of emotional intelligence (EI) in the process of mediation. Using a phenomenological research methodology simulating doctor–patient disputes mediated with an AI Smart ODR system in place of a human mediator, we found an association between EI and the propensity for a participant to change their previously asserted claims. Our results indicate participants with lower EI tend to prolong resolution compared to those with higher EI. Future research include trialling larger scale ODR systems for specific cohorts of patients in the area of health related dispute resolution are advanced. [ABSTRACT FROM AUTHOR]

The Knowledge Discovery from Databases (KDD) technique called 'association rules' is applied to a large data set representing applicants for government-funded legal aid. Results indicate that KDD can be an invaluable tool for legal analysts. Association rules discovered identify associations between variables that are present in the data set though are not necessarily causal. Interesting rules can prompt analysts to formulate hypotheses for further investigation. The identification of interesting rules is typically performed using an objective measure of 'interesting' although this measure is often not sufficiently accurate to eliminate all uninteresting rules. In this article, a subjective measure of interestingness is adopted in conjunction with the objective measures. This leads to the ability to focus more accurately on those rules that surprise the analyst and are therefore more likely to be interesting. In general, KDD techniques have not been applied to law despite possible benefits because data is often stored in narrative form rather than in structured databases. However, the impending introduction of data warehouses that collect data from a number of organizations across a legal system presents invaluable opportunities for analysts using KDD. [ABSTRACT FROM AUTHOR]