HCC-Medium: StepGreen: Mobilizing Social Networks and Context Awareness to Motivate Reduced Energy

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In 2005, Americans consumed 100 quadrillion BTUs of energy, or almost six times the world wide average per person. Much of this energy consumption is directly related to personal, individual activities such as lighting, heating and cooling. By making simple modifications to these routine activities individuals can conserve energy and help reduce total CO2 emissions. This project leverages Internet technologies to develop a scalable approach to changing behavior regarding environmental footprint (the amount of natural resources or emissions required to support an individual or household). The intent is to use online social networks, cell phones and other technologies to provide a set of ecologically sound, context-sensitive behavioral recommendations. The ultimate goal is to achieve Internet-scale energy behavior change via behavioral research on successful ways to motivate change, environmental impact analysis, and ubiquitous computing that supports objective measurement and context-sensitive communication. The project will use the existing StepGreen.org website as a testbed for three core activities. First, controlled field studies will be conducted to examine the value of personalization and social influence on motivation to change as well as how motivational strategies can accommodate differences among ethnic and cultural groups. Second, inexpensive sensing techniques will be developed that can unobtrusively extract information about changes in daily behaviors. For example, this will be able to track home heating, cooling and transportation behavior through simple financial monitoring of transactions such as electricity bills and gasoline purchases. Finally, the StepGreen deployment, as a large-scale social intervention, must adapt flexibly to contextual information about people (e.g., favored communication modalities, appropriate timing). The multidisciplinary nature of the proposed work enables innovative changes in several scientific domains. By bringing together technical innovation and social science, the proposed work can test theories of social computing in the field, providing a detailed understanding of how online social networks in combination with behavioral intervention strategies can lead to widespread behavioral change. Simultaneously, this work will explore and innovate solutions for large-scale distributed evaluation of Ubicomp technology. By bringing together environmental science and machine learning, the investigators will create the first objective calculator of individual energy use. Finally, the research will benefit environmental decision making by identifying misconceptions about relationships between behavior and energy consumption, educating a broad populace on individual actions they can take to reduce their consumption, and, ideally, achieving reductions in U.S. energy use.Broader impacts. The proposed research will benefit education through the interdisciplinary training of graduate and undergraduate students and through high school outreach as part of Carnegie-Mellon's Green Design Apprenticeship. The work?s focus on different socioeconomic groups will help to highlight the importance of addressing cross-cultural issues in design and behavioral science. Finally, the project will benefit society by helping to address a critical social issue and by providing results that inform other domains in which societal benefits depend on individual behavior change (e.g., health, littering, community action).