Congist'26: Interdisciplinary Perspectives on Crisis

Between Skylla and Charybdis? AI-Governance in Higher Education Institutions Beyond Multi-Crisis

D2-S2-K1

14 May 2026, 11:05

20m

Kurul Odası (Istanbul University Faculty of Letters)

Oral Presentation Session 2.7 (Day 2)

Speakers

Marc-André Heidelmann (IU International University of Applied Sciences) Susanne Maria Weber (Philipps-University of Marburg)

Description

GenAI’s rapid development raises risks to be addressed by policymakers and organisations. Recent work highlights deepfakes, harmful digital ecosystems and security gaps in AI compliance frameworks (Madhavan et al. 2025).
In this multicrisis, strategies diverge: some prioritise rapid deployment and national security (Arora et al. 2025), others human rights (Weerts 2025) or a balance between industrial growth and ethics (Wang et al. 2025). Balancing innovation, safety and ethics and keeping transparency frameworks adaptable to regulatory gaps is central (Bertolini et al. 2024).
Ethical critiques and policy analyses call for international cooperation via the UN, Council of Europe and EU (Rudolph, Ismail & Popenici 2024; Slimi 2023; Garrido Rebolledo 2025). For example voluntary guidelines should become binding regulation (Tang et al. 2025). Codes of conduct stress early risk detection, transparency about abilities and limits, and labelling of AI content (BMDV 2023), highlighting tensions between innovation, markets and human rights.
Social justice, fairness and equity concerns shape responsible AI innovation in higher education (Figueiras 2024). Responsible use of tools such as ChatGPT requires risk mitigation, ethical use, data privacy, AI literacy and institutional policies, and should guide research on ethical implications, pedagogical uses, AI‑driven faculty development and their impact on academic integrity, teaching, learning and equity (Nguyen 2025).
AI can catalyse learning and examination cultures and push universities to reinvent themselves (Christ‑Brendemühl 2024). In our paper we address, how algorithmic governance demands revised philosophies, stronger risk management, staff competences and robust ethical‑legal norms. From an organisational education perspective (Göhlich et al. 2016), inclusive decision‑making, equitable capacity building, adaptive governance and trust‑building are key to legitimate AI governance globally (Weber & Heidelmann forthcoming).