Strengthening Co-Determination in Digital Transformation: A Qualitative Approach to Enhancing Works Councils’ AI Literacy and Capability for Socio-Ethical Reflection
Abstract The accelerating digital transformation, and particularly the diffusion of generative AI technologies, poses profound challenges for workplace co-determination. Works councils increasingly face the need to assess and negotiate technological innovations under conditions of epistemic asymmetry, time pressure, and limited experience in (socio)-technical reflection. This paper introduces the Implication Canvas, an adapted version of the Implication Fan developed at the Berlin Ethics Lab, as a participatory tool to strengthen deliberative capacity in co-determination contexts with a focus on socio-ethical reflection. Drawing on an explorative qualitative research design, including participatory observation and post-workshop surveys, the study examines iterative adaptations of the canvas in three workshops with a cooperating works council. Findings indicate that the adapted canvas facilitates structured reflection on preconditions, consequences, and solution pathways of AI-driven workplace innovations while bridging communicative and epistemic gaps between management, technical experts, and employee representatives. The study argues that effective and responsible co-determination should be understood as an integrative competence combining technical orientation, ethical reflexivity, and procedural agency. Participatory reflection tools such as the Implication Canvas can support the practical enactment of this competence and contribute to more inclusive and responsible workplace AI governance.
Authors
- Deniz Sarikaya (ORCID: https://orcid.org/0000-0001-8951-8161)
- Christian Herzog (ORCID: https://orcid.org/0000-0003-2513-2563)
- Robin Preiß (ORCID: https://orcid.org/0000-0001-5232-7222)
Publication Details
- Journal
- Digital Society
- Published
- 2026-09-22
- DOI
- https://doi.org/10.1007/s44206-026-00287-x
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00