ing, and significant changes in response to a constantly evolving set of circumstances.

There are, of course, many points of intersection across these areas. For example, eco-feedback devices within the home (a sociotechnical system) interact with the larger, smart grid system (part of the built infrastructure); personal mobile devices (relying on built infrastructure and deployed in a sociotechnical context) provide data that feed into more robust modeling (a crosscutting methodology itself); and so on. In addition, better information about what is happening at an individual or local level can inform broader policy making and decision making.

Smarter energy grids, sustainable agriculture, and resilient infrastructure provide three concrete and important examples of the potential role of IT innovation and CS research in sustainability.

• Moving toward smarter and more sustainable ways of providing electricity will require a rethinking of many aspects of society, including the fundamental electric grid. A forward-looking, sustainable grid scenario presents a fundamentally more cooperative interaction between demand and supply, as well as greater transparency throughout the energy supply chain, with the goal of achieving both deep reductions in peak demand and reductions in overall demand as well as deep penetration of renewables in the supply blend. Information and data management with regard to both time (demand, availability, and so on) and space are essential to making progress toward a smarter, more sustainable electric grid. Computer science research and methodological approaches (in areas including user interfaces and improved modeling and analytical tools) will be needed at all levels to address the broad systems challenges presented by the smart grid.

• With respect to agriculture, there is growing concern regarding whether agricultural productivity can keep pace with human needs. A sustainable food system will be key to ensuring that the world’s population receives necessary nutrition without additional damage being done to the environment and society. As with the electric grid, it is in the systems issues in sustainable agriculture that the opportunities for IT seem most salient. Approaches to a sustainable food system include taking a systems view of the challenge; developing methods for measuring the costs, benefits, and impacts of different agricultural systems; assisting in the use of precision agriculture to minimize needed inputs; making information accessible for informed consumption; and developing social networks for local food sourcing. As with the smart electric grid, information and data management are essential to making progress toward a smarter, more sustainable, global food system. Computer science research

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