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Ethical Issues in Big Data Analytics for Time Critical Mobility Forecasting

  • Gemma Galdon Clavell
  • Victoria PeuvrelleEmail author
Chapter
  • 17 Downloads

Abstract

Big data analytics for time critical mobility forecasting involves the use of large amounts of data from different sources, which are combined to gather new insights and foresee potential needs and developments. Due to this intensive use of data and the sensitivity of projects involving critical infrastructures and technologies, the use of big data analytics for time critical mobility forecasting has legal and ethical impacts and risks that need to be addressed and mitigated. While this may not be obvious at first glance in some cases, as the presence of personal data and direct impacts on individuals may be minimal, ethics issues are still relevant. These are related to the possible privacy- and security-related consequences, as well as potential misuse and “function creep”, both during product development and testing and in the actual use of the final product. This chapter thus seeks to tackle those ethical challenges as they were addressed by an expert ethics team in the EC-funded datAcron project. We start by explaining the efforts made at the EU level to ensure the ethical development of publicly funded technologies and the framework and risks all projects need take into account, and then we briefly go over the different insights and actions regarding the datAcron project to ensure the ethics compliance of the project. While the process and advice developed is specific to datAcron, we believe it holds lessons for other similar initiatives seeking to be aware of and comply with their ethics obligations.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Eticas Research and InnovationBarcelonaSpain

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