Rapid developments in artificial intelligence (AI) and automation technologies are set to have a significant impact on a broad range of professions. Advanced software systems with high degrees of autonomy will prospectively execute a broad range of functions, including high-skill and non-routine tasks like preparing tax reports, providing financial services or diagnosing diseases. These developments affect the way in which human workers execute their tasks, resulting in new challenges with regard to their ability to understand and evaluate machine-generated inputs.
Some studies suggest that the increasing automation will inevitably result in “job polarisation" leading: e.g., to a greater economic disparity between highly skilled jobs and low-skilled jobs which are too expensive to automate. What is more, the introduction of new technologies at the workplace will significantly alter the content and the organization of work, affecting working conditions, remuneration and hierarchies. Interacting with AI redefines skills and employees’ roles – and consequently this transformation needs to be shaped by political agents, trade unions, and worker activism.
In this summer school, we aim to explore upcoming research questions related to the emerging impacts of artificial intelligence at workers. By convening senior researchers and findings from ongoing PhD research we want to deepen our understanding about the methods to explore the empirical relevance and specifics of the phenomenon. We also want to situate individual research projects within the broader research agenda on the AI-based worker management and human-centred AI in the workplace.
We invite submissions related to the topics of algorithmic management, smart manufacturing, human-machine interaction, changes in management strategies, discrimination in the workplace, involvement of trade unions in regulating the use of AI, occupational safety and health risks, changes in work organization, requirements for workers’ training, and autonomy and risk monitoring.
Prof. Dr. Martin Krzywdzinski is a Professor of International Labour Relations at the Helmut Schmidt University in Hamburg, director at the Weizenbaum Institute for the Networked Society and head of the research group "Globalization, Work and Production" at the WZB Berlin Social Science Center.
Dr. Florian Butollo is a Research Fellow the WZB Berlin Social Science Center. Florian was a senior advisor at the Enquete Commission ‘Artificial Intelligence – Social Responsibility and Economic Potential’ of the German Parliament (2018 – 2020).
Dr. Milagros Miceli is a Research Lead of the newly funded research group Data, Algorithmic Systems, and Ethics at Weizenbaum-Institut. In her research, Milagros is interested in questions of meaning creation and symbolic power encoded in training data. Her work comprises ethnographic fieldwork with data annotators, collectors, and scientists in different sites around the world.
Dr. Miriam Rosa is a researcher and professor at Iscte-University Institute of Lisbon (CIS). She is a social and organizational psychologist, conducting research and training on relations between social groups of asymmetric status, and processes of social influence.
Please send a short CV (max. 3 pages) and an abstract of your paper (400 words max) by May 15, 2023.
Your abstract should contain the following subheadings:
Applications (in a single PDF file) must be submitted to inga.sabanova(at)fes.de by May 15, 2023.
The list of selected participants will be announced by June 15, 2023.
If you are selected you will be required to submit a manuscript of a full paper (4000 words, excluding footnotes and bibliography) by July 15, 2023 to inga.sabanova(at)fes.de
This is essential to ensure that participants get the most of this programme. Papers will be circulated in advance and allocated to peer discussants.
We kindly ask you to apply only if you accept these terms of conditions and are prepared to follow the guidelines and deadlines.
The best five papers will be published after the summer school.
Call for Participants
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