Thilo Hagendorff


Dr. Thilo Hagendorff is an expert in applied ethics, especially technology and AI ethics. He is the author of several books, associate member of the Cluster of Excellence "Machine Learning: New Perspectives for Science" at the University of Tuebingen, lecturer at the Hasso Plattner Institute at the University of Potsdam, speaker at various conferences and public events, as well as member of several working groups on AI governance. He was a visiting scholar at Stanford University as well as UC San Diego.

Personal website

www.thilo-hagendorff.info

Contact

AI Research Building
Maria-von-Linden-Str. 6
Room 30-5/A10
72076 Tuebingen

thilo.hagendorffspam prevention@uni-tuebingen.de
+49 7071 29-70814

Selected Publications

A complete list of my 50+ publications as well as books can be found here.

  • Hagendorff, Thilo; Fabi, Sarah; Kosinski, Michal (2022): Machine intuition: Uncovering human-like intuitive decision-making in GPT-3.5. In arXiv:2212.05206, pp. 1–19. (Link)
  • Hagendorff, Thilo; Bossert, Leonie N.; Tse, Yip Fai; Singer, Peter (2022): Speciesist bias in AI: how AI applications perpetuate discrimination and unfair outcomes against animals. In AI Ethics, pp. 1–18. (Link)
  • Hagendorff, Thilo (2022): A Virtue-Based Framework to Support Putting AI Ethics into Practice. In Philosophy & Technology 35 (3), pp. 1–246. (Link)
  • Hagendorff, Thilo; Danks, David (2022): Ethical and methodological challenges in building morally informed AI systems. In AI Ethics, pp. 1–14. (Link)
  • Hagendorff, Thilo (2022): AI ethics and its pitfalls: not living up to its own standards? In AI and Ethics, pp. 1–8. (Link)
  • Fabi, Sarah; Hagendorff, Thilo (2022): Why we need biased AI -- How including cognitive and ethical machine biases can enhance AI systems. In arXiv:2203.09911v1, pp. 1–25. (Link)
  • Hagendorff, Thilo (2022): Blind spots in AI ethics. In AI Ethics 2 (4), pp. 851–867. (Link)
  • Hagendorff, Thilo (2021): Linking human and machine behavior. A new approach to evaluate training data quality for beneficial machine learning. In Minds and Machines 31, pp. 563–593. (Link)
  • Hagendorff, Thilo; Meding, Kristof (2021): Ethical considerations and statistical analysis of industry involvement in machine learning research. In AI & SOCIETY - Journal of Knowledge, Culture and Communication, pp. 1–11. (Link)
  • Hagendorff, Thilo (2021): Forbidden knowledge in machine learning. Reflections on the limits of research and publication. In AI & SOCIETY - Journal of Knowledge, Culture and Communication 36 (3), pp. 767–781. (Link)
  • Helm, Paula; Hagendorff, Thilo (2021): Beyond the Prediction Paradigm. Challenges for AI in the Struggle Against Organized Crime. In Law and Contemporary Problems 84 (3), pp. 1–17. (Link)
  • Bossert, Leonie; Hagendorff, Thilo (2021): Animals and AI. The role of animals in AI research and application – An overview and ethical evaluation. In Technology in Society 67, pp. 1–7. (Link)
  • Hagendorff, Thilo (2020): The Ethics of AI Ethics. An Evaluation of Guidelines. In: Minds and Machines 30 (3), pp. 457–461. (Link)
  • Hagendorff, Thilo (2019): From privacy to anti-discrimination in times of machine learning. In: Ethics and Information Technology 33 (3), pp. 331–343. (Link)
  • Hagendorff, Thilo; Wezel, Katharina (2019): 15 challenges for AI: or what AI (currently) can’t do. In AI & SOCIETY - Journal of Knowledge, Culture and Communication 35 (2), pp. 355-365. (Link)

Talks and media appearances

Here are complete lists of my talks and media appearances.

Teaching

  • since 2019: Lecturer at the Hasso-Plattner-Institute at the University of Potsdam, seminars about ethics in data engineering and machine learning; evaluations resulted in the following overall grades: 1.7, 1.4, 1.1
  • since 2014: Lecturer at the University of Tuebingen, seminars on applied ethics, including information, media and technology ethics; evaluations, if they took place, resulted in the following overall grades: 1.1, 1.3, 1.1, 1.3, 1.5, 1.6, 1.3, 1.4