The Data-driven Society: Social, Political, and Ethical Aspects of Datafication
Det datadrivna samhället: Sociala, politiska och etiska aspekter av datafiering

TFRE65, 3.0 credits, G1 (First Cycle)

Valid for: 2025/26
Faculty: Faculty of Engineering LTH
Decided by: PLED L
Date of Decision: 2025-02-27
Effective: 2025-03-17

General Information

Depth of study relative to the degree requirements: First cycle, has only upper-secondary level entry requirements
Language of instruction: The course will be given in English

Aim

Our societies and lives are to an increasing extent datafied, and shaped by means of collecting, analysing and utilising digital data. As this transforming data landscape offers new opportunities for knowledge and action, it also involves novel forms of concerns and risks. This course offers an introduction to critical perspectives on datafication, how it impacts ways of knowing and living, and its social, ethical and political consequences. Moreover, the course aims to provide the students with an understanding of the interconnected relationship between the social and the technological. The course is divided into three modules, focusing on how to understand the datafied society, the data promises and perils and concludingly, ideas about the good data life.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

• be able to explain theoretical conceptualisations of digital data and datafied society
• master basic terminology in critical data studies
• demonstrate a basic understanding of sociotechnical implications of datafication and its significance for social, political and technical development
• demonstrate a basic understanding of the important societal and ethical considerations in data collection and the use of data for public good

Competences and skills
For a passing grade the student must

• be able to describe datafication as a concept and practice in relation to ideas about societies, politics, knowledge, and everyday life, including conflict areas of datafication
• understand, analyse and describe potential challenges in the light of social, political, ethical and governance implications of datafication in a societal context
• be able to discuss the course reading and lecture contents during seminars
• be able to present a short analysis in writing and orally.

Judgement and approach
For a passing grade the student must

• demonstrate a critical analytical approach to datafication.
• be able to identify different stakeholders and interests involved in datafied societies, with a particular focus on societal, political and ethical implications.

Contents

The course is designed as a lecture and seminar series, as well as an independent written work and oral presentation.

Examination details

Grading scale: UG - (U, G) - (Fail, Pass)
Assessment:

Participation in the course seminars is required (may be completed by make-up assignments). Understanding of the lecture material and course readings will be examined by 3 seminar discussions and 1 individual final essay and oral presentation.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Modules
Code: 0125. Name: Understanding the Datafied Society.
Credits: 0.5. Grading scale: UG - (U, G). Assessment: Participation in seminar
Code: 0225. Name: The Data Promises and the Data Perils.
Credits: 0.5. Grading scale: UG - (U, G). Assessment: Participation in seminar
Code: 0325. Name: The Good Data Life.
Credits: 0.5. Grading scale: UG - (U, G). Assessment: Participation in seminar
Code: 0425. Name: Final Essay and Presentation.
Credits: 1.5. Grading scale: UG - (U, G). Assessment: Individual essay and oral presentation during a seminar.

Admission

Admission requirements:

• First cycle, has only upper-secondary level entry requirements

Reading list

• Barocas, Solon., Hardt, Moritz. & Narayanan, Arvind. (2023). Chapter 8. Datasets, in Barocas, Solon., Hardt, Moritz. & Narayanan, Arvind. Fairness and machine [open access].
• Bigo, D., Isin, E., & Ruppert, E. (Eds.). (2019). Data Politics: Worlds, Subjects, Rights (1st ed.). Routledge. https://doi.org/10.4324/9781315167305 [open access] Selected sections.
• boyd, danah, & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society, 15(5), 662–679. https://doi.org/10.1080/1369118X.2012.678878.
• D'Ignazio, Catherine & Klein, Lauren F. (2020). Data feminism. Cambridge, Massachusetts: The MIT Press [open access] Selected sections.
• Iliadis, A., & Russo, F. (2016). Critical data studies: An introduction. Big Data & Society, 3(2). https://doi.org/10.1177/2053951716674238.
• Jarke, Juliane (eds.) (2024). Dialogues in Data Power: Shifting Response-Abilities in a Datafied World. Bristol: Bristol University Press [open access] Selected sections.
• Kitchin, Rob (2025) Critical Data Studies: An A to Z Guide to Concepts and Methods. Cambridge: Polity Books. [Open access] Selected entries.
• Loukissas, Y. A. (2019). All data are local: Thinking critically in a data-driven society. MIT Press. [open access] Selected sections.
• Van Dijck, José (2014) Datafication, dataism and dataveillance: Big data between scientific paradigm and ideology. Surveillance and Society 12(2): 197–208.
• Andreassen, Rikke, Kaun, Anne, & Nikunen, Kaarina. (2021). Fostering the data welfare state: A Nordic perspective on datafication. Nordicom Review, 42(2), 207–223. Optional reading.
• Bucher, Taina, 'Conclusion: Algorithmic Life', in Bucher T (2018) If...then : algorithmic power and politics. New York: Oxford University Press. [LU online access] Optional reading.
• Flensburg, Sofie, & Lomborg, Stine (2023). Datafication research: Mapping the field for a future agenda. New Media & Society, 25(6), 1451-1469. https://doi.org/10.1177/14614448211046616 . Optional reading.
• Jarke, Juliane, & Büchner, Stefanie (2024). Who cares about data? Data care arrangements in everyday organisational practice. Information, Communication & Society, 27(4), 702–718. https://doi.org/10.1080/1369118X.2024.2320917 . Optional reading.

Contact

Course coordinator: Charlotte Högberg, charlotte.hogberg@lth.lu.se
Examinator: Charlotte Högberg, charlotte.hogberg@lth.lu.se