Megaprojects, Affected communities and sustainability decision making

Increasing scrutiny from the wider community is contributing to a shift towards the delivery and operation of major projects that meets and maintains the sustainability priorities of the community. This is especially significant for large economic projects which have a global track record of social benefit shortfalls, cost overruns, and underestimation of risks. Major industrial and infrastructure projects that cost more than US$1 billion are typically called mega-projects. Globally, investment in mega-projects has exceeded $10 trillion in the last ten years. With so many projects in the pipeline -and many taking place in emerging economies – the effectiveness of the sustainability decision making process is particularly important. The purpose of this paper is to examine how the existing sustainability decision making processes and strategies address the potential challenges facing communities affected by mega-projects. It highlights issues with current operational level approaches to social sustainability assessment at the project level, and argues that to improve accountability and transparency of project outcomes, positive externalities that flow from goods and services provided by the social and cultural systems of the community must be incorporated into decision making.

Navigating the social dimension of sustainability decision making of mega-projects

Until recently, sustainable development was perceived as essentially an environmental issue, relating to the integration of environmental concerns into economic decision-making. As a result, environmental considerations have been the primary focus of sustainability decision making during the economic development process for major projects, and the assessment and preservation of social and cultural systems has been arguably too limited. The practice of social impact and sustainability assessment is an established and accepted part of project planning, however, these practices are not aimed at delivering sustainability outcomes for social systems, rather they are designed to minimise ‘unsustainability’ and contribute to project approval. Currently, there exists no widely recognised standard approach for assessing social sustainability and accounting for positive externalities of existing social systems in project decision making. As a result, very different approaches are applied around the world, and even by the same organisations from one project to another. This situation is an impediment not only to generating a shared understanding of the social implications as related to major projects, but more importantly, to identifying common approaches to help improve social sustainability outcomes of proposed activities. This paper discusses the social dimension of sustainability decision making of mega-projects, and argues that to improve accountability and transparency of project outcomes it is important to understand the characteristics that make some communities more vulnerable than others to mega-project development. This paper highlights issues with current operational level approaches to social sustainability assessment at the project level, and asserts that the starting point for project planning and sustainability decision making of mega-projects needs to include the preservation, maintenance, and enhancement of existing social and cultural systems. It draws attention to the need for a scoping mechanism to systematically assess community vulnerability (or sensitivity) to major infrastructure development during the feasibility and planning stages of a project.

From impact assessment to user-friendly risk management decision-making

In earlier cultures and societies, hazards and risks to human health were dealt with by methods derived from myth, metaphor and ritual. In modem society however, notions of hazard and risk have been transformed from the level of a folk discourse to that of an expert centred concept (Plough & Krimsky, 1987). With the professionalization of risk and hazard analysis came a preferred framework for decision making based on a range of 'technical' methodologies (Giere, 1991 ). This is especially true for decision processes relating to risk assessment and management, and impact assessment. Such approaches however, often entail narrow technical-based theoretical assumptions about human behaviour and the natural world, and the· methods used. They therefore carry 'in-built' error factors that contribute considerable uncertainty to the results.

Reasoning paradigms in legal decision support systems

In this paper we discuss the strengths and weaknesses of a range of artificial intelligence approaches used in legal domains. Symbolic reasoning systems which rely on deductive, inductive and analogical reasoning are described and reviewed. The role of statistical reasoning in law is examined, and the use of neural networks analysed. There is discussion of architectures for, and examples of, systems which combine a number of these reasoning strategies. We conclude that to build intelligent legal decision support systems requires a range of reasoning strategies.

Deductive, inductive and analogical reasoning in legal decision support systems

In this paper we provide an overview of a number of fundamental reasoning formalisms in artificial intelligence which can and have been used in modelling legal reasoning. We describe deduction, induction and analogical reasoning formalisms, and show how they can be used separately to model legal reasoning. We argue that these formalisms can be used together to model legal reasoning more accurately, and describe a number of attempts to integrate the approaches.

Freedom to choose? Embryo selection, reproductive decision-making and the role of the state

Involving the biopsy of an eight-cell embryo, PGD has been hailed as a means of making reproductive decisions without having to face the heart-wrenching decision to abort an affected foetus. However, controversy around the kinds of traits for which testing can be done, and who has access to the technology, has led to questions about the way in which the technology is developing. Women who are allowed to access in vitro fertilisation (IVF) services can currently also access PGD in limited circumstances.

Genetic technologies and the regulation of reproductive decision-making in Australia

This article provides a critical analysis of the current Australian regulatory landscape at the interface between genetics and reproductive decision- making. The authors argue that a comparative analysis with other countries and international law and a contextual examination of the way law regulates concepts such as disease and health, abnormality and normality is necessary before we can develop appropriate policy and legislative responses in this area. Specific genetic testing technologies are considered including prenatal genetic testing, preimplantation genetic diagnosis and inheritable genetic modification. An increasing number of members of the Australian community are using genetic testing technologies when they decide to have a baby. The authors argue that as concepts of disease and health vary among members of the community and the potential to test for traits other than illness increases, a new tension arises between an ethic of individual choice and a role for government in regulating reproductive decision-making.

Prenatal diagnosis, genetics and reproductive decision-making

Recent developments in genetic science will potentially have a significant impact on reproductive decision-making by adding to the list of conditions which can be diagnosed through prenatal diagnosis. This article analyses the jurisdictional variations that exist in Australian abortion laws and examines the extent to which Australian abortion laws specifically provide for termination of pregnancy on the grounds of fetal disability. The article also examines the potential impact of pre-implantation genetic diagnosis on reproductive decision-making and considers the meaning of reproductive autonomy in the context of the new genetics.

Enabling safe autonomous driving in real-world city traffic using multiple criteria decision making

This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.

Improving safety for driverless city vehicles : real-time communication and decision making

This paper elaborates on the Cybercars-2 Wireless Communication Framework for driverless city vehicles, which is used for Vehicle-to-Vehicle and Vehicle-to-Infrastructure communication. The developed framework improves the safety and efficiency of driverless city vehicles. Furthermore, this paper also elaborates on the vehicle control software architecture. On-road tests of both the communication framework and its application for real-time decision making show that the communication framework is reliable and useful for improving the safe operation of driverless city vehicles.

Towards increased road safety : real-time decision making for driverless city vehicles

This work elaborates on the topic of decision making for driverless city vehicles, particularly focusing on the aspects on how to develop a reliable approach which meets the requirements of safe city traffic. Decision making in this context refers to the problem of identifying the most appropriate driving maneuver to be performed in a given traffic situation. The overall decision making problem is decomposed into two consecutive stages. The first stage is safety-crucial, representing the decision regarding the set of feasible driving maneuvers. The second stage represents the decision regarding the most appropriate driving maneuver from the set of feasible ones. The developed decision making approach has been implemented in C++ and initially tested in a 3D simulation environment and, thereafter, in real-world experiments. The real-world experiments also included the integration of wireless communication between vehicles.

eHealth-as-a-Service (eHaaS) : a data-driven decision making approach in Australian context

A commitment in 2010 by the Australian Federal Government to spend $466.7 million dollars on the implementation of personally controlled electronic health records (PCEHR) heralded a shift to a more effective and safer patient centric eHealth system. However, deployment of the PCEHR has met with much criticism, emphasised by poor adoption rates over the first 12 months of operation. An indifferent response by the public and healthcare providers largely sceptical of its utility and safety speaks to the complex sociotechnical drivers and obstacles inherent in the embedding of large (national) scale eHealth projects. With government efforts to inflate consumer and practitioner engagement numbers giving rise to further consumer disillusionment, broader utilitarian opportunities available with the PCEHR are at risk. This paper discusses the implications of establishing the PCEHR as the cornerstone of a holistic eHealth strategy for the aggregation of longitudinal patient information. A viewpoint is offered that the real value in patient data lies not just in the collection of data but in the integration of this information into clinical processes within the framework of a commoditised data-driven approach. Consideration is given to the eHealth-as-a-Service (eHaaS) construct as a disruptive next step for co-ordinated individualised healthcare in the Australian context.