1. Home
  2. Team
  3. Vertrauenswürdige Künstliche Intelligenz
  4. Hendrik Heuer

Prof. Dr.-Ing. Hendrik Heuer

Forschungsprofessor

Portrait von Hendrik Heuer

Hendrik Heuer ist Forschungsprofessor am CAIS. Er leitet das Forschungsprogramm Design vertrauenswürdiger Künstlicher Intelligenz. Seine Forschung hat folgende Schwerpunkte:

  • Vertrauen in Künstliche Intelligenz durch Verständnis, Kontrolle und Mitgestaltung
  • Partizipative Softwareentwicklung für Maschinelles Lernen
  • Kampf gegen Misinformation und Desinformation

Lebenslauf

  • 2023–2024: Vertretung der Professur für Angewandte Informatik, Universität Bremen
  • 2020–2024: Wissenschaftlicher Mitarbeiter (Postdoc), Universität Bremen
  • 2022: Postdoctoral Research Fellow, Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), Harvard University
  • 2020: Promotion „Users & Machine Learning-Based Curation Systems“
  • 2016–2020: Wissenschaftlicher Mitarbeiter (Doktorand), Universität Bremen
  • Von 2009 bis 2014 Studium von Digitalen Medien (Medieninformatik), Human-Computer Interaction und Machine Learning an der Universität Bremen, der SUNY University at Buffalo, dem KTH Royal Institute of Technology (Stockholm) und der Aalto University (Helsinki)

  • Heuer, H. et al. (2024): Algorithmic Regimes: Methods, Interactions, and Politics. Digital Studies Series. Amsterdam University Press.

  • Benharrak, K., Zindulka, T., Lehmann, F., Heuer, H., & Buschek, D. (2024). Writer-Defined AI Personas for On-Demand Feedback Generation. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (CHI ’24). https://arxiv.org/abs/2309.10433

  • Jarke, J., Prietl, B., Egbert, S., Boeva, Y., Heuer, H., & Arnold, M. (2024). Algorithmic Regimes: Methods, Interactions, and Politics. Amsterdam University Press. https://doi.org/10.2307/jj.11895528

  • Jarke, J., & Heuer, H. (2024). Reassembling the Black Box of Machine Learning: Of Monsters and the Reversibility of Foldings. In Algorithmic Regimes: Methods, Interactions, and Politics. Amsterdam University Press. https://doi.org/10.2307/jj.11895528.7

  • Eslami, M., & Heuer, H. (2024). Revisiting Transparency Efforts in Algorithmic Regimes. In Algorithmic Regimes: Methods, Interactions, and Politics. Amsterdam University Press. https://doi.org/10.2307/jj.11895528.4

  • Altay, S., Berriche, M., Heuer, H., Farkas, J., & Rathje, S. (2023). A survey of expert views on misinformation: Definitions, determinants, solutions, and future of the field. Harvard Kennedy School (HKS) Misinformation Review, 4(4), 34. https://doi.org/10.37016/mr-2020-119

  • Heuer, H., & Glassman, E. L. (2023). Accessible Text Tools for People with Cognitive Impairments and Non-Native Readers: Challenges and Opportunities. Proceedings of Mensch Und Computer 2023, 250–266. https://doi.org/10.1145/3603555.3603569

  • Heuer, H., & Glassman, E. L. (2022). A Comparative Evaluation of Interventions Against Misinformation: Augmenting the WHO Checklist. Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI ’22), 1–21. https://doi.org/10.1145/3491102.3517717

  • Heuer, H., Jarke, J., & Breiter, A. (2021). Machine learning in tutorials—Universal applicability, underinformed application, and other misconceptions. Big Data & Society, 8(1). https://doi.org/10.1177/20539517211017593

Weitere anzeigen

  • Heuer, H. (2022). Human-Computer Interaction & Machine Learning For A Better Society. Collaboration and Computer-Human Interaction Group, Aarhus University, Aarhus, Denmark.

  • Heuer, H. (2022). Towards Socio-Technical Interventions Against Misinformation. Science and Art of Simulation (SAS 2022): Trust and Disinformation. High-Performance Computing Center Stuttgart, Stuttgart, Germany.

  • Heuer, H. (2022). Wie Künstliche Intelligenz schwierige Texte verständlicher machen kann. Künstliche Intelligenz und Teilhabe, Bremen, Germany.

  • Heuer, H. (2022). Leibniz Media Lunch Talks. Leibniz-Institut für Medienforschung – Hans-Bredow Institut, Hamburg, Germany.

  • Heuer, H., Jarke, J., Breiter, A. (2021). Machine Learning in Tutorials – Universal Applicability, Underinformed Application, and Other Misconceptions. Re-Situating Learning: Making Sense of Data, Media and Dis/Unities of Practice. Annual Conference of the Collaborative Research Centre 1187 “Media of Cooperation”, University of Siegen, Siegen, Germany.

  • Heuer, H. (2021). Audit, Don’t Explain – Recommendations Based on a Socio-Technical Understanding of Machine Learning-Based Systems, Leipzig Symposium on Intelligent Systems (LEISYS), Lancaster University Leipzig, Leipzig, Germany.

  • Heuer, H. (2021). Basement Talk on Explainable AI. KU Leuven, Leuven, Belgium.

  • Heuer, H. (2021). Open University Lunchtalk. Open University, Milton Keynes, UK.

Prof. Dr.-Ing. Hendrik Heuer

Forschungsprofessor

E-Mail: hendrik.heuer@cais-research.de

Bereich: Vertrauenswürdige Künstliche Intelligenz
CAIS Team