Functions and consequences of artificial intelligence
in the science and higher education organization
Innovation analysis and transfer development
KIWIT is an interdisciplinary and inter-university research network.
Funded by the Federal Ministry for Research, Technology and Space (BMFTR).
© 2025 NBS Northern Business School for KIWIT. Email: forschungsgruppe.kiwit[at]uol.de
Research class led by Prof. Dr. Stefan Kühl, with staff members Bernd Eckstein and Dennis Düllmann, as well as Prof. Dr. Marcel Schütz.
Offer for researchers and early-career researchers
Digitalization processes in organizations
classify and understand
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Four-semester course at Bielefeld University
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Weekly focused text discussions online
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Regular information on texts and authors is provided on this page
In this research class, designed to run over four semesters, approximately 100 key texts on the topic of organization and digitalization are discussed on a weekly basis. The research class is part of the Bielefeld Graduate School in History and Sociology and is embedded in the KIWIT research group. Due to participation from multiple locations, the seminar is conducted online via Zoom.
For each session, all participants read a selected text, which is then discussed jointly. Prior reading is required for meaningful participation. Attendance is flexible, and participants may join any sessions or discussions that are of interest to them. The research seminar is primarily aimed at doctoral researchers at Bielefeld University and its project partners who are actively engaged in relevant research, but it is also open to interested master’s students and advanced bachelor’s students who have already completed the introductory module in organizational sociology. External researchers from other universities as well as other interested participants with a thematic focus are also welcome. Registration with brief information about one’s background and motivation is required (see information below)
27.04.2026: Hedfeld, D. P., Lammers, D. A., & Kamieth, F. (2025). Künstliche Intelligenz und Corporate Governance.
Gallery | click/swipe
Wenn KI-Systeme zur „Black Box“ im Unternehmen werden, bedarf es neuer Mechanismen der Überwachung und Transparenz.
KI-Systeme gehen weit über operative Abläufe hinaus und verändern zunehmend das Fundament unternehmerischer Entscheidungsfindung, Risikoanalyse und Kontrollstrukturen.
Wenn KI-Systeme zur „Black Box“ im Unternehmen werden, bedarf es neuer Mechanismen der Überwachung und Transparenz.
In der nächsten Research Class diskutieren wir einen Beitrag von Patrick Hedfeld, Alexander Lammers und Felix Kamieth, der die Auswirkungen von KI auf die Corporate Governance beleuchtet. Ausgangspunkt ist die Beobachtung, dass KI-Systeme weit über operative Abläufe hinausgehen und zunehmend das Fundament unternehmerischer Entscheidungsfindung, Risikoanalyse und Kontrollstrukturen verändern können.
Die Autoren schlagen vor, KI-Governance nicht als rein technisches Problem, sondern als strategische Führungsaufgabe zu verstehen. Dabei rücken ethische Anforderungen, die Vermeidung von Algorithmic Bias und die Einhaltung regulatorischer Rahmenbedingungen wie des EU AI Acts in den Fokus. Ein zentraler Aspekt ist die Transformation der Rechenschaftspflicht: Wie lässt sich die Verantwortung des Managements sicherstellen, wenn komplexe Algorithmen Entscheidungsgrundlagen liefern, die für menschliche Akteure oft nur schwer nachvollziehbar sind?
Damit eröffnet der Text eine organisationsübergreifende Perspektive auf die Gestaltung verantwortungsvoller Governance-Strukturen: Wenn KI-Systeme zur „Black Box“ im Unternehmen werden, bedarf es neuer Mechanismen der Überwachung und Transparenz. Hedfeld et al. zeigen, dass sich durch den KI-Einsatz die Anforderungen an die Fachkompetenz und die Kontrollpflichten von Vorständen und Aufsichtsräten verschieben – insbesondere dort, wo Effizienzgewinne gegen ethische Risiken und rechtliche Haftungsfragen abgewogen werden müssen.
Dr. Patrick Hedfeld und Dr. Alexander Lammers arbeiten auf dem Gebiet der Corporate Governance und Transformation, Felix Kamieth ergänzt diese Perspektive um die organisatorischen Implikationen digitaler Kontrollsysteme. Gemeinsam forschen und beraten sie an der Schnittstelle von regulatorischen Anforderungen und der praktischen Implementierung von KI in Unternehmensstrukturen.
Duration
Winter Semester 2025/2026 – Winter Semester 2027/2028
Schedule
Mondays, 4:15 p.m. (via Zoom)
Seminar Guidelines
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Sessions begin punctually at 4:15 p.m.
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The KIWIT Research Class, planned as a two-year program, meets weekly during the semester on Mondays from 4:15 to 6:00 p.m. and is conducted online via a consistent Zoom link (provided upon registration). Each session is based on a text that all participants are expected to have read in advance. Participation without prior engagement with the assigned—at times demanding—text is strongly discouraged.
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Participants attending for the first time are asked to briefly introduce themselves in the chat, addressing the following points: institutional affiliation, specific interests in the field of digitalization (and, where applicable, artificial intelligence), and current research projects.
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The seminar does not follow a formal moderation structure; instead, contributions are organized organically via Zoom’s raise-hand function.
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When more than five participants are present (which is typically the case), microphones should remain muted. In sessions with a particularly large number of participants, a small-group discussion phase of approximately 20 minutes may be scheduled to facilitate closer engagement with the text. The guiding questions remain constant: Which arguments are convincing? Where do doubts or unresolved issues remain? During small-group discussions, participants are encouraged to keep their microphones switched on.
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If authors of the assigned texts are present, they are kindly asked to refrain from participating in the discussion during the first 60 minutes. This will be followed by an opportunity for extended commentary and reflection.
Registration
Those interested in participating in the Research Class are requested to send an email with brief information about their academic background and motivation to Prof. Dr. Stefan Kühl (stefan.kuehl[at]uni-bielefeld.de). Registered participants will be added to the mailing list
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