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Mandatory readings

Beaulieu, A., & Leonelli, S. (2021). Data and society. A critical introduction. Sage. The book is also available as a preprint at , 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.

Fundamental Rights Agency (2019). Data quality and artificial intelligence – mitigating bias and error to protect fundamental rights. (pp. 20).

Gerdes, A. (2021). A participatory data-centric approach to AI Ethics by Design. Applied Information Intelligence.

Redman, T.C. (2018). If your data is bad, your machine learning tools are useless. Harvard Business Review.

Taylor, L. (2017). What is data justice? The case for connecting digital rights and freedoms globally. Big Data & Society,Ìý4(2).Ìý (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).

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,Ìý3(2).Ìý

Masso, A., Tiidenberg, K.,Ìý& Siibak, A. (eds) (2020), How to Understand the Datafied World? A Methodological Guide (27 pages). Tallinn: Tallinn University Press. Available at: