This talk examines ethical challenges and guiding principles that arise when AI-based systems become entangled in research methodologies. With a focus on qualitative research methods and ethics research, the presentation addresses key ethical dimensions — including scientific integrity, algorithmic bias, sustainability and dependency, as well as human agency and oversight — and asks what fundamentally changes for qualitative research ethics when AI enters the picture. Based on current discussions and practical examples from our own research, we conclude by proposing concrete strategies for responsibly addressing these challenges.

Simon David Hirsbrunner (University of Tübingen) is a social scientist and media scholar serving as team leader at the International Center for Ethics in the Sciences and Humanities (IZEW), University of Tübingen. He holds a Master’s degree in International Relations from the Graduate Institute of International and Development Studies (Geneva), a Master’s degree in European Media Studies from the University of Potsdam and the University of Applied Sciences Potsdam, and a PhD in Media Ethnography from the University of Siegen.
His research examines ethical dimensions of artificial intelligence, with a particular focus on the intersections of AI, ethics, and sustainability, as well as high-risk application domains including education, predictive policing, and automated recruiting. He frequently employs inventive, digital, and mixed-methods approaches in his work.
Beyond research, Dr. Hirsbrunner lectures in AI ethics at the Hasso Plattner Institute / University of Potsdam and advises institutions and stakeholders — including the German Rectors‘ Conference (Hochschulrektorenkonferenz), police departments, educators, and companies — on the responsible development, deployment, and use of AI systems