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  1. An elemental ethics for artificial intelligence: water as resistance within AI’s value chain.Sebastián Lehuedé - forthcoming - AI and Society:1-14.
    Research and activism have increasingly denounced the problematic environmental record of the infrastructure and value chain underpinning artificial intelligence (AI). Water-intensive data centres, polluting mineral extraction and e-waste dumping are incontrovertibly part of AI’s footprint. In this article, I turn to areas affected by AI-fuelled environmental harm and identify an ethics of resistance emerging from local activists, which I term ‘elemental ethics’. Elemental ethics interrogates the AI value chain’s problematic relationship with the elements that make up the world, critiques the (...)
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  • Of dog kennels, magnets, and hard drives: Dealing with Big Data peripheries.Zane Griffin Talley Cooper - 2021 - Big Data and Society 8 (2).
    How did the 3.5-inch Winchester hard disk drive become the fundamental building block of the modern data center? In attempting to answer this question, I theorize the concept of "data peripheries" to attend to the awkward, uneven, and unintended outsides of data infrastructures. I explore the concept of data peripheries by first situating Big Data in one of its many unintended outsides—an unassuming dog kennel in Indiana housed in a former permanent magnet manufacturing plant. From the perspective of this dog (...)
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  • Data that warms: Waste heat, infrastructural convergence and the computation traffic commodity.Julia Velkova - 2016 - Big Data and Society 3 (2).
    This article explores the ways in which data centre operators are currently reconfiguring the systems of energy and heat supply in European capitals, replacing conventional forms of heating with data-driven heat production, and becoming important energy suppliers. Taking as an empirical object the heat generated from server halls, the article traces the expanding phenomenon of ‘waste heat recycling’ and charts the ways in which data centre operators in Stockholm and Paris direct waste heat through metropolitan district heating systems and urban (...)
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  • Data journeys: Capturing the socio-material constitution of data objects and flows.Paula Goodale, Yu-Wei Lin & Jo Bates - 2016 - Big Data and Society 3 (2).
    In this paper, we discuss the development and piloting of a new methodology for illuminating the socio-material constitution of data objects and flows as data move between different sites of practice. The data journeys approach contributes to the development of critical, qualitative methodologies that can address the geographic and temporal scale of emerging knowledge infrastructures, and capture the ‘life of data’ from their initial generation through to re-use in different contexts. We discuss the theoretical development of the data journeys methodology (...)
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  • Practicing, materialising and contesting environmental data.Jennifer Gabrys - 2016 - Big Data and Society 3 (2).
    While there are now an increasing number of studies that critically and rigorously engage with Big Data discourses and practices, these analyses often focus on social media and other forms of online data typically generated about users. This introduction discusses how environmental Big Data is emerging as a parallel area of investigation within studies of Big Data. New practices, technologies, actors and issues are concretising that are distinct and specific to the operations of environmental data. Situating these developments in relation (...)
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  • The material consequences of “chipification”: The case of software-embedded cars.M. C. Forelle - 2022 - Big Data and Society 9 (1).
    Today's modern car is an assemblage of mechanical and digital components, of metal panels that comprise its structure and silicon chips that run its functions. Communication and information studies scholars have interrogated the problematic aspects of the programs that run those functions, revealing serious issues surrounding privacy and security, worker surveillance, and racial, gendered, and class-based bias. This article contributes to that work by taking a step back and asking about the issues inherent not in the software running on these (...)
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