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Data, Politics and Society provides an interdisciplinary introduction to the politics and ethics of using large-scale, primarily human-generated, data, drawing together insights from data science, political geography, legal studies and sociology. The course focuses on the critical theories and ethical debates currently occurring around the role of data, data science and technology within our society 鈥� often from a geographic perspective. The module does not only focus on how geographical thinking can provide a way of conceptualising these debates, but also looks at the opportunities within current data science research to help address or counter the pre-conceived socio-economic and historical narratives data science is at risk of exacerbating.

The course covers five broad topics:

1. Data: The Good, The Bad, The Ugly
2. Societal and political implications of data and technology
3. Regulations and governance
4. Crowdsourcing, VGI, and Geographic Citizen Science
5. Critical Data Studies

Over the ten weeks, the course provides an extensive introduction into the implications of using large-scale, human-generated datasets both from a research and a societal perspective. Through an exploration of recent case studies within the technology industry and academia, we will first explore the good, the bad, and the ugly side of such datasets. With this in mind, we look at the societal implications and challenges of new data and technologies in more general terms. We then provide an introduction to current data protection regulation and highlight inadequacies in addressing some these challenges. Alternative strategies of using large-scale data and technology for scientific research will be explored by looking at crowdsourcing and Volunteered Geographic Information methods. In the final week of the course, we explore how the societal challenges and implications of using large-scale datasets have led to the emergence of a Critical Data Studies.

You will gain:

• A theoretical and practical understanding of the opportunities and implications of using large-scale datasets, including the inherent and explicit biases within the data and within the algorithms trained on them.
• Practical approaches to addressing these limitations and how to frame data science analyses, including introducing accounting for ethical issues into the data science workflow.
• An awareness of the emerging data science regulatory environment, including the role of data privacy within academic research and the significance of current and future legislative frameworks within the U.K. and further afield for data science applications.
• An understanding of how the implications of using large-scale datasets, have led to the development of a Critical Data Studies as well as current debates within this domain.

The course usually consists of 10 lectures and 10 seminars, within which active class discussion is facilitated and peer-to-peer learning is encouraged. We combine, for example individual presentations and contributions with small-group discussions on data bias in published academic papers.

Pre-requisites

None.

Transferable skills

This course will provide those interested in social and geographic data science as well as data ethics with a comprehensive background in the complexities of using large-scale human-generated datasets. You will gain practical experience in: dealing with 鈥淏ig data鈥� from a theoretical point of view; giving presentations and practising verbal communication through the weekly interactive seminars; and critical thinking. At the end of the course, students will have written a commentary article on a topic of their choice to consolidate these skills.

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