Data Science, Statistics, and Civic Statistics: Education for a Fast Changing World

Jim Ridgway (), Pedro Campos () and Rolf Biehler ()
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Jim Ridgway: School of Education, University of Durham
Pedro Campos: LIAAD-INESC TEC and University of Porto
Rolf Biehler: Institute of Mathematics, Paderborn University

Chapter Chapter 22 in Statistics for Empowerment and Social Engagement, 2022, pp 563-580 from Springer

Abstract: Abstract What is the relationship between data scienceData science, statistics, and Civic Statistics? Are they symbiotic, or are they in conflict? A graphic on the homepage of the American Statistical Association ( https://www.amstat.org/ASA/about/home.aspx?hkey=6a706b5c-e60b-496b-b0c6-195c953ffdbc ) reads BIGTENT statistics+data science, indicating their intended direction of travel—statistics and data science need to live together. Products of data science (including social media) have transformed modern life. We outline the idea of disruptive socio-technical systems (DST)Socio-technical systems (DST)—new social practices that have been made possible by innovative technologies, and which have profound social consequences—and we point to some examples of technologies that are, or have capacity to facilitate DST. Civic Statistics aims to address pressing social issues, and data science has created new concerns and also new approaches to work on social issues. Here, we argue that this should go beyond simply addressing known problems, and should include empowering citizens to engage in discussions about our possible futures, including the regulation of potential and actual DST. These are exciting times; there are new approaches to knowing about and understanding the world, many of them associated with data science, and students need to engage with these important epistemological issues as a key element in Civic Statistics skills. Here, we relate features of data science to features of Civic Statistics, and to dimensions of knowledge relevant to Civic Statistics. From the viewpoint of Civic Statistics, we argue that we have a responsibility to prepare students for their roles as spectators (understanding the nature and potential of data science products in creating DST), and as referees (having a political voice about which DST are acceptable and unacceptable), and as players (engaging with data science for their own and others’ benefit). We elaborate on the skills needed for these roles. We argue that citizens should use ideas and tools from data science to improve their lives and their environments.

Keywords: Data science; Disruptive technologies; Machine learning; Curriculum reform; Participatory science; Citizen science (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-20748-8_22

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DOI: 10.1007/978-3-031-20748-8_22

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