Data and Society

Mandatory readings

Beaulieu, A., & Leonelli, S. (2021). Data and society. A critical introduction. Sage. The book is also available as a preprint at https://ore.exeter.ac.uk/repository/bitstream/handle/10871/127993/Data%20and%20Society_Preprint.pdf?sequence=2, but page numbering differs from the print version. The book is available at Göteborgs universitetsbibliotek for article copies.

Selected chapters:

Chapter 3, pp. 35-50
Chapter 4, pp. 51-64
Chapter 7, pp. 116-134
Chapter 10, pp. 184-201

Dencik, L., Hintz, A., Redden, J., & Treré, E. (2019). Exploring Data Justice: Conceptions, Applications and Directions. Information, Communication & Society, 22(7), 873–881. https://doi.org/10.1080/1369118X.2019.1606268

Fundamental Rights Agency (2019). Data quality and artificial intelligence – mitigating bias and error to protect fundamental rights. (pp. 20). https://fra.europa.eu/en/publication/2019/data-quality-and-artificial-intelligence-mitigating-bias-and-error-protect

Gerdes, A. (2021). A participatory data-centric approach to AI Ethics by Design. Applied Information Intelligence. https://doi.org/10.1080/08839514.2021.2009222

Redman, T.C. (2018). If your data is bad, your machine learning tools are useless. Harvard Business Review. https://hbr.org/2018/04/if-your-data-is-bad-your-machine-learning-tools-are-useless

Taylor, L. (2017). What is data justice? The case for connecting digital rights and freedoms globally. Big Data & Society, 4(2). https://doi.org/10.1177/2053951717736335 (pp.14)

Elective readings

Batrinca, B., Treleaven, P.C. Social media analytics: a survey of techniques, tools and platforms. AI & Soc 30, 89–116 (2015). https://doi.org/10.1007/s00146-014-0549-4

Cinnamon, J. (2019). Data inequalities and why they matter for development. Information Technology for Development. DOI: 10.1080/02681102.2019.1650244

Gabrys, J., Pritchard, H., & Barratt, B. (2016). Just good enough data: Figuring data citizenships through air pollution sensing and data stories. Big Data & Society, 3(2). https://doi.org/10.1177/2053951716679677

Masso, A., Tiidenberg, K., & Siibak, A. (eds) (2020), How to Understand the Datafied World? A Methodological Guide (27 pages). Tallinn: Tallinn University Press. Available at: https://ssrn.com/abstract=4034321