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PeopleFahimi, Miriam

Profile Picture: Dr. Miriam Fahimi MF
Profile Picture of Dr. Miriam Fahimi; Research Team Cryo Cultures © Can Gülcü

Dr. Miriam Fahimi ( Researcher)

Keywords: Critical Algorithm Studies, Critical Data Center Studies, Science and Technology Studies, Feminist & Care Theory


Bio

Miriam Fahimi (or Mina) is an STS scholar researching AI and its infrastructures. At Paderborn University, her work examines data centers as socio-material infrastructures, their environmental and societal effects, as well as their political epistemologies.

Before joining Paderborn University, she was a visiting scholar at the Department of Science and Technology Studies at Cornell University (USA), a research fellow at the Center for Advanced Internet Studies in Bochum (Germany), and a Marie Skłodowska-Curie Fellow in the EU Horizon 2020 project NoBIAS – Artificial Intelligence without Bias. Her research and policy engagement focused on AI justice, algorithmic discrimination and bias, fair and transparent AI, and EU AI governance.

She earned her PhD from the University of Klagenfurt (Austria), where she ethnographically studied how computer scientists are materially and semantically shaping the emerging notions of fair and transparent AI.

Miriam is a non-resident fellow with Cornell’s Digital Due Process Clinic, a member of STS Austria, and part of netzforma e.V. – Association for Feminist Internet Policy. Together with Dr. Raphaële Xenidis, she is the co-lead of the CAIS working group Standardising Justice in the Algorithmic Society. Exploring Standardisation Practices for Artificial Intelligence Systems in the European Union.


Selected Publications

Fahimi, M., State L., Kasirzadeh, A. (forthcoming). From Explaining to Diagnosing: A Justice-Oriented Framework of Explainable AI for Bias Detection. Vol. 8 No. 1 (2025): Proceedings of the Eight AAAI/ACM Conference on AI, Ethics, and Society (AIES-25)

Fahimi, M., & Kinder-Kurlanda, K. (2025). Friction in the Materialities of Value. Relating Transparency, Algorithms and Credit Scoring. In M. Burkhardt, T. Seitz, C. Ochs, & J. Kropf (Eds), Frictions: Conflicts, controversies and design alternatives in digital valuation (pp. 141–159). transcript.

Xenidis, R., & Fahimi, M. (2025). Standardising Equality in the Algorithmic Society? A Research Agenda. Proceedings of Fourth European Workshop on Algorithmic Fairness, 310–314. https://proceedings.mlr.press/v294/xenidis25a.html

Link to full publication list:
https://scholar.google.com/citations?user=4aJkfsUAAAAJ&hl=de