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Technical University of Munich

Carmen Löfflad, Ph.D.

Carmen Löfflad is a post-doctoral researcher at the Chair of Cyber Trust.

Her research focuses on the implications of algorithmic systems, with a focus on those used to shape human behaviors and address collective action problems. By analyzing behavioral, perceptual, and societal effects, she aims to inform the debate around the ethical design, regulation, and governance of algorithmic technologies.

She was involved in the research project “Learning from the 'Frontrunner'? A Multidisciplinary Analysis of the Chinese Social Credit System and its Impact on Germany” of the Bavarian Research Institute for Digital Transformation (bidt).

She holds a Doctoral Degree (Dr. rer. nat) from the Technical University of Munich, a Master of Science in Management & Technology from the Technical University of Munich and a Bachelor of Arts in European Business from the Technical University of Applied Sciences of Regensburg.

Email: carmen.loefflad(at)tum.de | Phone: +49 (89) 289 - 18580

Publications

Journal Articles
  • Loefflad, C., Chen, M., & Grossklags, J. (2025) Citizen Involvement in Algorithmic Regulation: How Awareness and Participation Shape Public Opinion, Civic Behaviors and Social Trust. Human Behavior and Emerging Technologies, forthcoming.
  • Loefflad, C., Chen, M., & Grossklags, J. (2024) Reputational Discrimination and Fairness in China's Social Credit System. Digital Government: Research and Practice, 5(4), Article No. 40. Publisher Version (Open Access)
Conference Proceedings
  • Loefflad, C., Chen, M., & Grossklags, J. (2024) Social Scoring Systems for Behavioral Regulation: An Experiment on the Role of Transparency in Determining Perceptions and Behaviors. Proceedings of the 7th AAAI/ACM Conference on AI, Ethics, and Society (AIES), pp. 891-904. Acceptance rate = 31.8%. Publisher Version (Open Access) Supplementary File.
  • Loefflad, C. (2024) Automated Decision-Making Systems for Behavioral Regulation: Understanding Perceptions and Behavioral Reactions. Proceedings of the 7th AAAI/ACM Conference on AI, Ethics, and Society (AIES) - Student Abstracts, pp. 28-31. Publisher Version (Open Access)
  • Loefflad, C., & Grossklags, J. (2024) How the Types of Consequences in Social Scoring Systems Shape People's Perceptions and Behavioral Reactions. Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT), pp. 1515-1530. Acceptance rate = 24.1% (725 submissions, 175 accepted full papers) Publisher Version (Open Access)
  • Loefflad, C., Chen, M., & Grossklags, J. (2023). Factors Influencing Perceived Legitimacy of Social Scoring Systems: Subjective Privacy Harms and the Moderating Role of Transparency. Proceedings of the International Conference on Information Systems (ICIS). Complete Research Paper. Publisher Version Author Version. Supplementary File. Nominee – Best Paper Award (complete and short papers; 1380 submissions; 387 accepted papers).

Doctoral Dissertation

Loefflad, C. (2025) On Human Reactions to Social Scoring Systems. Technical University of Munich

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