Government as a social machine - the implications of government as a social machine for making and implementing market-based policy

This is the second of two reports from the Government as a Social Machine project. The first report gave an overview of the evolution of electronic/digital government, and explored the concept of 21st century government as a \u27social machine\u27. This report identifies seven social machines developed by governments in Australia and New Zealand. These social machines harness digital technologies in order to deliver more effective and efficient services, develop better business practices, and enable better accountability and transparency. The report gives an overview of each social machine in context, describing the social need that is being met and the community that has developed it, and begins to unravel some of the socio-political consequences that might arise from the use of these social machines within the public policy context. These reports are not intended to be comprehensive (further educational materials are being developed as part of the ANZSOG Case Library), but they are intended to begin a conversation amongst those studying or practicing in public policy as to how governments can better understand, manage and employ these evolving social machines for better governance and social benefit

2017 Texas Bays and Estuaries Meeting

Program for the 2017 Texas Bays and Estuaries Meeting held in Port Aransas, Texas, April 12-13, 2017.Coastal Bend Bays & Estuaries Program, Coastal Bend Bays Foundation, The University of Texas Marine Science Institute, Sea Grant Texas at Texas A&M University, Harte Research Institute for Gulf of Mexico Studies, and Mission Aransas National Estuarine Research Reserve.Marine Scienc

The role of forest genetic resources in responding to biotic and abiotic factors in the context of anthropogenic climate change

The current distribution of forest genetic resources on Earth is the result of a combination of natural processes and human actions. Over time, tree populations have become adapted to their habitats including the local ecological disturbances they face. As the planet enters a phase of human-induced climate change of unprecedented speed and magnitude, however, previously locally-adapted populations are rendered less suitable for new conditions, and ‘natural’ biotic and abiotic disturbances are taken outside their historic distribution, frequency and intensity ranges. Tree populations rely on phenotypic plasticity to survive in extant locations, on genetic adaptation to modify their local phenotypic optimum or on migration to new suitable environmental conditions. The rate of required change, however, may outpace the ability to respond, and tree species and populations may become locally extinct after specific, but as yet unknown and unquantified, tipping points are reached. Here, we review the importance of forest genetic resources as a source of evolutionary potential for adaptation to changes in climate and other ecological factors. We particularly consider climate-related responses in the context of linkages to disturbances such as pests, diseases and fire, and associated feedback loops. The importance of management strategies to conserve evolutionary potential is emphasised and recommendations for policy-makers are provided

The Mundane Computer: Non-Technical Design Challenges Facing Ubiquitous Computing and Ambient Intelligence

Interdisciplinary collaboration, to include those who are not natural scientists, engineers and computer scientists, is inherent in the idea of ubiquitous computing, as formulated by Mark Weiser in the late 1980s and early 1990s. However, ubiquitous computing has remained largely a computer science and engineering concept, and its non-technical side remains relatively underdeveloped. The aim of the article is, first, to clarify the kind of interdisciplinary collaboration envisaged by Weiser. Second, the difficulties of understanding the everyday and weaving ubiquitous technologies into the fabric of everyday life until they are indistinguishable from it, as conceived by Weiser, are explored. The contributions of Anne Galloway, Paul Dourish and Philip Agre to creating an understanding of everyday life relevant to the development of ubiquitous computing are discussed, focusing on the notions of performative practice, embodied interaction and contextualisation. Third, it is argued that with the shift to the notion of ambient intelligence, the larger scale socio-economic and socio-political dimensions of context become more explicit, in contrast to the focus on the smaller scale anthropological study of social (mainly workplace) practices inherent in the concept of ubiquitous computing. This can be seen in the adoption of the concept of ambient intelligence within the European Union and in the focus on rebalancing (personal) privacy protection and (state) security in the wake of 11 September 2001. Fourth, the importance of adopting a futures-oriented approach to discussing the issues arising from the notions of ubiquitous computing and ambient intelligence is stressed, while the difficulty of trying to achieve societal foresight is acknowledged

Challenges in Complex Systems Science

FuturICT foundations are social science, complex systems science, and ICT. The main concerns and challenges in the science of complex systems in the context of FuturICT are laid out in this paper with special emphasis on the Complex Systems route to Social Sciences. This include complex systems having: many heterogeneous interacting parts; multiple scales; complicated transition laws; unexpected or unpredicted emergence; sensitive dependence on initial conditions; path-dependent dynamics; networked hierarchical connectivities; interaction of autonomous agents; self-organisation; non-equilibrium dynamics; combinatorial explosion; adaptivity to changing environments; co-evolving subsystems; ill-defined boundaries; and multilevel dynamics. In this context, science is seen as the process of abstracting the dynamics of systems from data. This presents many challenges including: data gathering by large-scale experiment, participatory sensing and social computation, managing huge distributed dynamic and heterogeneous databases; moving from data to dynamical models, going beyond correlations to cause-effect relationships, understanding the relationship between simple and comprehensive models with appropriate choices of variables, ensemble modeling and data assimilation, modeling systems of systems of systems with many levels between micro and macro; and formulating new approaches to prediction, forecasting, and risk, especially in systems that can reflect on and change their behaviour in response to predictions, and systems whose apparently predictable behaviour is disrupted by apparently unpredictable rare or extreme events. These challenges are part of the FuturICT agenda