Risk-informed decision-making in the presence of epistemic uncertainty

An important issue in risk analysis is the distinction between epistemic and aleatory uncertainties. In this paper, the use of distinct representation formats for aleatory and epistemic uncertainties is advocated, the latter being modelled by sets of possible values. Modern uncertainty theories based on convex sets of probabilities are known to be instrumental for hybrid representations where aleatory and epistemic components of uncertainty remain distinct. Simple uncertainty representation techniques based on fuzzy intervals and p-boxes are used in practice. This paper outlines a risk analysis methodology from elicitation of knowledge about parameters to decision. It proposes an elicitation methodology where the chosen representation format depends on the nature and the amount of available information. Uncertainty propagation methods then blend Monte Carlo simulation and interval analysis techniques. Nevertheless, results provided by these techniques, often in terms of probability intervals, may be too complex to interpret for a decision-maker and we, therefore, propose to compute a unique indicator of the likelihood of risk, called confidence index. It explicitly accounts for the decisionmaker’s attitude in the face of ambiguity. This step takes place at the end of the risk analysis process, when no further collection of evidence is possible that might reduce the ambiguity due to epistemic uncertainty. This last feature stands in contrast with the Bayesian methodology, where epistemic uncertainties on input parameters are modelled by single subjective probabilities at the beginning of the risk analysis process.

Incorporating uncertainty in predictive species distribution modelling

Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

Older people and legal advice – the need for joined up and creative approaches

This paper reports the findings from research conducted with older people in Northern
Ireland which investigated whether their needs for legal information and advice were
being met. One of the unique aspects of the research involved investigating the
potential of the internet as a possible source for advising older people in relation to
legal problems. The findings suggest that online legal information may frequently assist
older people in identifying potential answers to their legal questions, but may not be an
adequate substitute for personal communication and advice. The research also
highlights the need for professionals to work together to meet the needs of older
persons for legal advice and to safeguard their interests. Such ‘joined up’ approaches
are particularly important, for example at the point of dementia diagnosis, where
information sharing between health and social care professionals may significantly
promote the legal and welfare interests of older people at a vulnerable point in their
lives. This paper therefore turns to work by university-based legal clinics in the United
States, such as the Elder Law Clinic at Pennsylvania State University, where social
work or healthcare professionals, lawyers and law students collaborate to support older
people in their search for resolution of legal problems.

BAILII, Legal Education and Open Access to Law

The British and Irish Legal Information Institute (BAILII) entered the online legal information landscape in 2001 with charitable status as a provider of UK and European judgments, and has over the past decade or so moved from a system quickly put together with any materials which could be found, to a system which provides a core resource to professionals in law. In this article we provide an overview for the law teacher of the system’s first years and we then look at whether usage in law schools has matched that of the professional, how the JISC funded Open Law project enabled development for law students, and where we might go in the future as part of the Legal Information Institute collective which operates under the ‘Free Access to Law’ banner.
As members of the Open Law team who sought funding, carried out the research and implemented the project, it seems to us that the project was generally successful. Our indications were that prior to Open Law the use of BAILII by students was low – it was not readily found or discussed by lecturers, was difficult to use, and generally less user friendly than it could have been. The changes implemented by Open Law appear to have changed that position considerably. However, our findings also indicate that there is much work to do to re-energise digital legal information as a legal education research field.

Web Services and Incerta Spiriti: A Game Theoretic Approach to Uncertainty

A web-service is a remote computational facility which is made available for general use by means of the internet. An orchestration is a multi-threaded computation which invokes remote services. In this paper game theory is used to analyse the behaviour of orchestration evaluations when underlying web-services are unreliable. Uncertainty profiles are proposed as a means of defining bounds on the number of service failures that can be expected during an orchestration evaluation. An uncertainty profile describes a strategic situation that can be analyzed using a zero-sum angel-daemon game with two competing players: an angel a whose objective is to minimize damage to an orchestration and a daemon d who acts in a destructive fashion. An uncertainty profile is assessed using the value of its angel daemon game. It is shown that uncertainty profiles form a partial order which is monotonic with respect to assessment.