GOVERNANCE OF DIGITAL MARKETS AND TECHNOLOGIES IN EUROPE

The course reviews key theories and approaches to assess and critically analyse the transformations introduced by digitalisation and datafication across markets and organisations. Particular attention is given to how data is produced, structured, and interpreted, and how these processes shape what can be known, measured, and governed in digital environments. The course aims to provide students with up-to-date theoretical frameworks, governance models, and real-life cases to discuss the impact of digital technologies on our society.

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At the end of the course, the students will be able to: (1) Demonstrate knowledge on the laters digital governance models and mechanisms adopted in the EU and beyond (2) Making judgements to assess the role of data and digital technology in transforming organizational and market practices. (3) Apply the understanding gained from the course to identify novel governance solutions for digital technologies (3) Critically examine the socio-technical aspects of technologies (4) Develop a critical awareness of the opportunities and risks of data-based innovation for the economy and society (5) Apply the analytical framework gained from the course to assess the societal implications of digitalization using real-life cases and scenarios.

The course reviews theories and approaches to critically assess the far-reaching transformations introduced by digitalisation and datafication across markets, organisations, and governance systems. It examines the socio-technical, political, and economic dimensions of digital transformation by engaging with key paradigms of the digital economy and the governance of digital technologies. Particular attention is devoted to the role of digital platforms, data infrastructures, and AI systems in reshaping contemporary forms of organisation, culture, and power. The course combines theoretical and empirical perspectives to explore topics such as digital transformation and the platform economy; Google as a cultural institution; the tokenised economy; the history and development of Artificial Intelligence; Langdon Winner’s theory of the politics of artifacts; the politics of data and biometric data; and the governance of digital technologies through emerging regulatory frameworks, including the Digital Markets Act (DMA) and the AI Act.

Key Reading: Alaimo, C. and Kallinikos, J. (2020) Managing by data: Algorithmic categorization and organizing, Organization Studies, online first https://journals.sagepub.com/doi/pdf/10.1177/0170840620934062. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? https://doi.org/10.1145/3442188.3445922 Cameron, F. R. (2021). Parker G. Van Alstyne M. & Choudary S. P. (2016) Platform Revolution. New York: Norton. Subramaniam, M. (2021). The 4 Tiers of Digital Transformation. Harvard Business Review. Winner, L. (1986). “Do artifacts have politics?” in The Whale and the Reactor: A Search for Limits in an Age of High Technology. Chicago: University of Chicago Press, Chapter 2, 19-39 The complete list of readings will be given at the beginning of the course.

The course includes a mix of frontal lectures, group discussions and case studies and will use a variety of innovative student-centred teaching methods. Lectures will make students familiar with theories, methods and analytical frameworks to help them gain knowledge on digital economy principles. Seminars will allow students to apply the knowledge they gain from the lecture through the discussion of a variety of real-life cases and scenarios. They will also let students practically work in teams and will help them gaining a number of soft skills such as collaborative and communicative skills and the ability to think creatively and critically about real-life cases and scenarios.

Students will be assessed based on: Mid-term Written Exam (30%); Final Oral Exam (70%). Non-attending students will be assigned supplementary readings.

A minimum of 28/30 as a final exam mark, demonstrated interest in the subject attested by a relevant thesis proposal, and good writing and analytical skills.