Lecture Series “Learning (in) Digital Media”
The lecture series focuses on the connection between learning and digital media. Processes of learning are a locus of organization, stabilization as well as perturbation of societal structures. The sociomateriality of such processes can be traced within the historic variability of infrastructure. As digital media have transformed the parameters of communal practice and participation, practices of learning have been re-situated to settings that are infrastructurally stabilized, yet locally and socially distributed, establishing new communities of practice. Recent interests in machine learning in the field of artificial intelligence lead to new agents of learning which challenge conventional notions of learning and transform conditions of communality. Furthermore, changing technologies of cooperation, instruction and learning also impact the terms of cooperation across social and cultural realms, challenging or reinforcing asymmetries of power. Hierarchies of knowledge and modes of political power are thereby inscribed into techniques and technologies of learning and cooperation and it seems that they are becoming increasingly difficult to trace, let alone undo. Yet the actual process of learning remains a communal practice, in which results of interaction cannot be fully predetermined.
The lecture series aims at examining the cooperative production of “learning” as a media and data practice in its different aspects: from the learning subjects, organizations and data practices involved in learning processes to self-learning systems and artificial intelligence. We invite scholars from several fields of research to inquire different practices and concepts of cooperative learning and learning in cooperation.
Possible questions include (but are not limited to):
- How are digital media shaping practices of learning?
- How is reciprocity within processes of learning implemented in digital media?
- What role do hegemonic structures play within these infrastructures on a level of practices?
- If participation is a fundamental condition of digital operations, how is the reciprocal openness of processes of learning affected by this?
- How are digital practices of learning affected by algorithmic biases and how can computers be taught to unlearn?
- How is the relationship of learning and forgetting altered by digital media and what could practices of forgetting look like?
- How does the notion of “error-making” as crucial part in the process of human learning translate – if at all – into a cooperative Machine Learning-based environment?
Lecture Series
“Learning (in) Digital Media”
2021/22
#1 Human-Aided Artificial Intelligence: Machinic capture of human labor in contemporary media culture
Tue, 12.10.21 | 6.00-8.00 PM | Hybrid
Rainer Mühlhoff (University of Osnabrück)
#2 Scaffolding and monitoring: Aspects of learning in the social design of explainable AI systems
Tue, 19.10.21 | 6.00-8.00 PM | Hybrid
Katharina Rohlfing (University of Paderborn)
#3 Towards a maturity-oriented education on the algorithms behind geomedia technologies
Tue, 02.11.21 | 6.00-8.00 PM | Hybrid
Inga Gryl (University Duisburg-Essen) and Helena Atteneder (University of Tübingen)
#4 Digital education and the IT industry
Tue, 09.11.21 | 6.00-8.00 PM | Hybrid
Petra Missomelius (University of Innsbruck)
#5 Governed by edtech? Valuing educational autonomy in a platform society
Tue, 16.11.21 | 6.00-8.00 PM | Online
Niels Kerssens (Utrecht University)
#6 Collaborating with machines: Researchers Meet ML-Algorithms
Tue, 23.11.21 | 6.00-8.00 PM | Online
Gabriele Gramelsberger (RWTH Aachen)
#7 On ground truths, biases, and morality in machine learning design and application
Tue, 30.11.21 | 6.00-8.00 PM | Online
Florian Jaton (University of Lausanne)
#8 Speculative approaches, cultures of surveillance, and digital futures in higher education
Thu, 13.01.22 | 6.00-8.00 PM | Online
Jen Ross (University of Edinburgh)
#9 Feminist Data Set
Thu, 27.01.22 | 6.00-8.00 PM | Online
Caroline Sinders
#10 Causality and the Future of Deep Learning
Tue, 01.02.22 | 6.00-8.00 PM | Online
M. Beatrice Fazi (University of Sussex)