In the midst of “algorithmic social machines”: model and metaphor for critical media education?
The datafication of everyday life and the use of algorithms in social decision-making processes are increasingly shaping lifeworld and society. Critical learning and education about the related social changes contribute to “digital enlightenment” and self-determination.
In this context, the project wants to take up the concept and metaphor of the “algorithmic social machine” and develop it for critical media education practice. As an explanatory model, this conceptual framework brings together application-oriented experiences from Web Science as well as results from Critical Data Studies and Science and Technology Studies.
As a metaphor, the “social machine” opens up diverse projection and reflection surfaces for questioning phenomena and processes of datafication. If this metaphorical concept is deconstructed, normative-ethical questions arise about the underlying image of humanity and the notion of the social world as a machine.
As a result, a conceptual essay with visualisations provides insights into the ‘machine room’ in which a ‘generator’ generates questions for critical media education practice.
Main results
After research and conceptual consolidation, a concept of an “algorithmic social machine” was developed that can be used in critical media education and that vividly interlocks and models individual and social datafication processes. First drafts for the visualization of the concept were presented and discussed in a workshop with educational practitioners and scientists. This opened up suggestions for improvement and possible test fields in adult education. In lectures and presentations, for example at the University of Cologne (Nov 2022), adult education associations (Feb 2023) as well as in the context of the Critical Big Data and Algorithmic Literacy Network (bigdataliteracy.net, Oct 2022), the concept, its critical metaphors and educational practical application potentials were also discussed. In the form of an essay, the description of the concept idea is available in a special issue for educational practice („Digitalisierung und Politikunterricht“ in German).
At the Global Media Forum 2023 in Bonn, the machine metaphor served as an introduction for a session on current results in digital journalism research.
The concept of the Algorithmic Social Machine will be presented at the joint annual conference of the specialist groups Media Education and Visual Communication of the Deutsche Gesellschaft für Publizistik und Kommunikationswissenschaft (DGPuK, Munich, Oct 2023).
Research focus
- Digital literacies
- Theories of media education
- Big Data
- Scoring
Curriculum Vitae
- Head of research at the Grimme Institute, collaboration in projects of the Grimme Research College at the University of Cologne
- Head of project development, authorised signatory ecmc Europäisches Zentrum für Medienkompetenz gGmbH (1997-2010)
- Studied Communication Studies, Philosophy at the University of Essen (M.A. 1993) and Fulbright Scholar at the New School, NYC (M.A., USA, 1995)
Lectures and publications
Gapski, H. (2022, 22 Nov.). “Of life in the ‘data-driven, algorithmic social machine’ and the implications for critical media education”. Lecture in the context of the lecture series “Media & Education” at the University of Cologne
Gapski, H. (2022). Fields of Discussion in Media Education: Datafied Lifeworlds and Data Protection. In Sander, U., von Gross, F., Hugger, KU. (Eds.) Handbuch Medienpädagogik . Springer VS, Wiesbaden. DOI: 10.1007/978-3-658-23578-9_82
Gapski, H. (2021): Artificial intelligence (AI) and critical media education. Expertise for the project “Digital Germany”.
Gapski, H.; Packard, S. (eds.).(2021). Super-scoring? Data-driven social technologies as a new educational challenge. Munich: kopaed. Full text (open access). DOI: 10.25656/01:22048.
Gapski, H. (2019): More than digital literacy. In: From Politics and Contemporary History. 69. Jg, 27-28, pp. 24-29. full text (open access).
Gapski, H.; Tekster, T.; Elias, M. (2018). Education for and about Big Data. Expert opinion in the context of ABIDA – Assessing Big Data. Marl: Grimme Institute. Full text (open access). DOI: 10.25656/01:17187.
Gapski, H. (2018): Big Data and Social Work. Contexts, examples and perspectives from a communication studies perspective. In: Hammerschmidt, Sagebiel, Hill & Beranek (eds.): Big Data, Facebook, Twitter & Co. and Social Work. Weinheim, Basel: Juventa. S. 75-94.
Gapski, H.; Oberle, M & Staufer, W. (eds.). (2017). Media literacy. Challenge for politics, political education and media education. bpb Schriftenreihe Vol. 10111. Bonn. Full text (open access).
Gapski, H. (2017): 1.0, 2.0, 3.0 and 4.0 – and what does media education count? In: S. Eder; C. Mikat; A. Tillmann (eds.): Software takes command. Challenges of “datafication” for media education in theory and practice. Series Schriften zur Medienpädagogik, Vol. 53. Munich: kopaed. S. 35-48.
Gapski, H. (2015)(ed.): Big Data and Media Education. Between loss of control, self-defence and sovereignty in the digital world. (=Schriftenreihe zur Digitalen Gesellschaft NRW, Vol. 3). Munich/Düsseldorf: kopaed. Full text (open access) DOI: 10.25656/01:11634.