Datafied Society
A.Y. 2024/2025
Learning objectives
The main objective of this course is to provide students the fundamental skills for critically reflecting on the 'datafied' society, a new social order based on the systematic extraction, aggregation and manipulation of data about people.
Datafication - which is understood as a process that is gradually affecting both market-oriented services (i.e. Airbnb, Uber etc.) and public services (such as education and health) - rests on two interrelated key factors: platforms and algorithms. Digital platforms are programmable architectures designed to shape the way we live and how social, political, cultural and economic life is organized. Platforms operate through algorithms which automatically classify extracted data ordering the social world, and are able to learn from data making predictions.
The process of datafication is however negotiated and resisted by users in their everyday life. In particular, the course will discuss the ambivalent nature of contemporary digital activism, proving that media imaginaries and technological myths can be used either to repress and hide authoritarianism or to reinvent democracy.
Datafication - which is understood as a process that is gradually affecting both market-oriented services (i.e. Airbnb, Uber etc.) and public services (such as education and health) - rests on two interrelated key factors: platforms and algorithms. Digital platforms are programmable architectures designed to shape the way we live and how social, political, cultural and economic life is organized. Platforms operate through algorithms which automatically classify extracted data ordering the social world, and are able to learn from data making predictions.
The process of datafication is however negotiated and resisted by users in their everyday life. In particular, the course will discuss the ambivalent nature of contemporary digital activism, proving that media imaginaries and technological myths can be used either to repress and hide authoritarianism or to reinvent democracy.
Expected learning outcomes
By the end of the course, students should have acquired the following skills: the ability to critically discuss the concept of (commercial) platform and algorithm; knowledge of a multi-layered perspective on platformisation including the micro-level of single platforms, the meso-level of the platform ecosystem and the macro-level of platform geopolitics; familiarity with a situated epistemology of algorithms moving beyond the popular conception of the latter as a black box; awareness of the algorithmic shaping of society; comprehension of users agency and resistance vis-à-vis digital platforms and collective efforts to democratise the datafied society. The final exam aims to verify the expected learning outcomes in relation to: knowledge and understanding of the main concepts developed in the debate on the Datafied society, critical presentation of case studies and empirical results related to the topics discussed during the course.
Lesson period: First trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
First trimester
Course syllabus
To introduce the main working mechanisms of the Datafied Society, the course will cover three main topics:
1) The platformisation of society;
2) The ambiguous nature of algorithms and Big Data in a datafied society;
3) Individual Agency and ethical challenges in the process of datafication.
To begin with, the course will analyse the role of digital platforms as the key infrastructures in the digital society and as the engines of the datafication of society. The discussion will focus on the features of the platforms, their functioning mechanisms, and the ethical challenges arising from the clash between digital platforms' value systems and the public interest.
Then, the focus will shift to algorithms, Big Data and AI in order to deepen the understanding of how individuals relate with data in the context of the datafied society. In particular, the discussion will deal with algorithmic situated nature, cultural perception and working mechanisms, as well as with the role they play as sources of new forms of discrimination and inequality.
Finally, the course will investigate users' agency and resistance vis-à-vis digital platforms in the datafied society, looking at ongoing reflections and experimentations on the possibilities to democratise the datafied society and realise fairer algorithms.
Students attending the course will be asked to deliver oral presentations on the topics mentioned above.
1) The platformisation of society;
2) The ambiguous nature of algorithms and Big Data in a datafied society;
3) Individual Agency and ethical challenges in the process of datafication.
To begin with, the course will analyse the role of digital platforms as the key infrastructures in the digital society and as the engines of the datafication of society. The discussion will focus on the features of the platforms, their functioning mechanisms, and the ethical challenges arising from the clash between digital platforms' value systems and the public interest.
Then, the focus will shift to algorithms, Big Data and AI in order to deepen the understanding of how individuals relate with data in the context of the datafied society. In particular, the discussion will deal with algorithmic situated nature, cultural perception and working mechanisms, as well as with the role they play as sources of new forms of discrimination and inequality.
Finally, the course will investigate users' agency and resistance vis-à-vis digital platforms in the datafied society, looking at ongoing reflections and experimentations on the possibilities to democratise the datafied society and realise fairer algorithms.
Students attending the course will be asked to deliver oral presentations on the topics mentioned above.
Prerequisites for admission
The knowledge acquired by the student who attended the first terms of the degree program in Public and Corporate Communication facilitates the understanding of concepts and theories covered in the course of Datafied Society.
Teaching methods
Frontal lessons (first weeks only) and oral presentations by students with active involvement in the class.
Teaching Resources
Mandatory Readings for attending students:
The reading list will be specified on the Ariel platform.
Mandatory Readings for non-attending students:
J. Van Dijck, T. Poell, M. De Waal (2018). The platform society: Public values in a connective world. Oxford: Oxford University Press.
T. Bucher (2018). If...Then. Algorithmic Power and Politics. Oxford: Oxford University Press.
Bonini T and Treré E (2024) Algorithms of Resistance: The Everyday Fight against Platform Power. The MIT Press. Note: the book is available in open-access format at https://doi.org/10.7551/mitpress/14329.001.0001.
The reading list will be specified on the Ariel platform.
Mandatory Readings for non-attending students:
J. Van Dijck, T. Poell, M. De Waal (2018). The platform society: Public values in a connective world. Oxford: Oxford University Press.
T. Bucher (2018). If...Then. Algorithmic Power and Politics. Oxford: Oxford University Press.
Bonini T and Treré E (2024) Algorithms of Resistance: The Everyday Fight against Platform Power. The MIT Press. Note: the book is available in open-access format at https://doi.org/10.7551/mitpress/14329.001.0001.
Assessment methods and Criteria
Assessment methods for attending students:
The evaluation will be based on: a) an oral in-class presentation on concepts and case studies related to the topics of the course (50%); b) a position paper on a specific debate on the Datafied Society (50%).
Assessment methods for non-attending students:
The evaluation will be based on a written exam with open-ended questions, assessing knowledge and critical understanding of the main concepts developed in the debate on the Datafied society. Answers will be evaluated taking into consideration: synthesis, clarity and argumentative quality, exhaustiveness and competence in the use of specialistic terminology.
Further information on the assessments for attending and non-attending students is provided on the Ariel platform.
The evaluation will be based on: a) an oral in-class presentation on concepts and case studies related to the topics of the course (50%); b) a position paper on a specific debate on the Datafied Society (50%).
Assessment methods for non-attending students:
The evaluation will be based on a written exam with open-ended questions, assessing knowledge and critical understanding of the main concepts developed in the debate on the Datafied society. Answers will be evaluated taking into consideration: synthesis, clarity and argumentative quality, exhaustiveness and competence in the use of specialistic terminology.
Further information on the assessments for attending and non-attending students is provided on the Ariel platform.
SPS/08 - SOCIOLOGY OF CULTURE AND COMMUNICATION - University credits: 9
Lessons: 60 hours
Professors:
Gerosa Alessandro, Keeling Silvia
Educational website(s)
Professor(s)