5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      The ethics of smart cities and urban science

      Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
      The Royal Society

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          <p class="first" id="d1923018e125">Software-enabled technologies and urban big data have become essential to the functioning of cities. Consequently, urban operational governance and city services are becoming highly responsive to a form of data-driven urbanism that is the key mode of production for smart cities. At the heart of data-driven urbanism is a computational understanding of city systems that reduces urban life to logic and calculative rules and procedures, which is underpinned by an instrumental rationality and realist epistemology. This rationality and epistemology are informed by and sustains urban science and urban informatics, which seek to make cities more knowable and controllable. This paper examines the forms, practices and ethics of smart cities and urban science, paying particular attention to: instrumental rationality and realist epistemology; privacy, datafication, dataveillance and geosurveillance; and data uses, such as social sorting and anticipatory governance. It argues that smart city initiatives and urban science need to be re-cast in three ways: a re-orientation in how cities are conceived; a reconfiguring of the underlying epistemology to openly recognize the contingent and relational nature of urban systems, processes and science; and the adoption of ethical principles designed to realize benefits of smart cities and urban science while reducing pernicious effects. </p><p id="d1923018e127">This article is part of the themed issue ‘The ethical impact of data science’.</p>

          Related collections

          Most cited references19

          • Record: found
          • Abstract: found
          • Article: found

          Smart cities of the future

            Bookmark
            • Record: found
            • Abstract: not found
            • Book: not found

            The Data Revolution: Big Data, Open Data, Data Infrastructures & Their Consequences

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Unique in the Crowd: The privacy bounds of human mobility

              We study fifteen months of human mobility data for one and a half million individuals and find that human mobility traces are highly unique. In fact, in a dataset where the location of an individual is specified hourly, and with a spatial resolution equal to that given by the carrier's antennas, four spatio-temporal points are enough to uniquely identify 95% of the individuals. We coarsen the data spatially and temporally to find a formula for the uniqueness of human mobility traces given their resolution and the available outside information. This formula shows that the uniqueness of mobility traces decays approximately as the 1/10 power of their resolution. Hence, even coarse datasets provide little anonymity. These findings represent fundamental constraints to an individual's privacy and have important implications for the design of frameworks and institutions dedicated to protect the privacy of individuals.
                Bookmark

                Author and article information

                Journal
                Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
                Phil. Trans. R. Soc. A
                The Royal Society
                1364-503X
                1471-2962
                November 14 2016
                November 14 2016
                : 374
                : 2083
                : 20160115
                Article
                10.1098/rsta.2016.0115
                5124065
                28336794
                e5e75f5a-1565-4178-81c0-01365acd5b14
                © 2016

                http://royalsocietypublishing.org/licence

                History

                Comments

                Comment on this article