Vasilis Kostakis, Alex Pazaitis, Minas V. Liarokapis
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引用次数: 0
Abstract
Technological imaginaries have been increasingly shaping the future perceptions of cities. From artificial intelligence and distributed ledger technology to three-dimensional printing, high-tech artifacts are very often the premises of such imaginaries. However, technology does not only refer to artifacts. Technology also encompasses the processes around the artifacts: how the artifacts are designed, manufactured, used, maintained, and disposed. From this perspective, high-tech visions often disregard problems that pertain to resource extraction, labor exploitation, energy use, and material flows. On the contrary, low-tech and localized alternatives incite lower impact and higher resilience visions. However, they fail to offer solutions of the desired scale and intensity. To address this tension, we provide an alternative vision for mid-tech: a balance between the opposite extreme qualities of low-tech and high-tech. Through a case of open-source prosthetics, we illustrate how to synergistically combine the efficiency and versatility of high-tech solutions with the potential for autonomy and resilience that low-tech offers. Then we discuss a mid-tech approach for distributed ledger technology from a city as a license lens. We provide connections with existing or conceptual applications to show how distributed ledger technology could support more socially and ecologically responsible data practices for city governance.
期刊介绍：
Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government.
BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices.
BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.
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