| The ethics of AI ethics: An evaluation of guidelines T Hagendorff Minds and machines 30 (1), 99-120, 2020 | 1513 | 2020 |
| 15 challenges for AI: or what AI (currently) can’t do T Hagendorff, K Wezel Ai & Society 35, 355-365, 2020 | 93 | 2020 |
| Artificial intelligence governance and ethics: global perspectives A Daly, T Hagendorff, L Hui, M Mann, V Marda, B Wagner, W Wang, ... arXiv preprint arXiv:1907.03848, 2019 | 78* | 2019 |
| To explain or not to explain?—Artificial intelligence explainability in clinical decision support systems J Amann, D Vetter, SN Blomberg, HC Christensen, M Coffee, S Gerke, ... PLOS Digital Health 1 (2), e0000016, 2022 | 70 | 2022 |
| Blind spots in AI ethics T Hagendorff AI and Ethics 2 (4), 851-867, 2022 | 63 | 2022 |
| Machine psychology: Investigating emergent capabilities and behavior in large language models using psychological methods T Hagendorff arXiv preprint arXiv:2303.13988, 2023 | 51 | 2023 |
| A virtue-based framework to support putting AI ethics into practice T Hagendorff Philosophy & Technology 35 (3), 55, 2022 | 41 | 2022 |
| Co-design of a trustworthy AI system in healthcare: deep learning based skin lesion classifier RV Zicari, S Ahmed, J Amann, SA Braun, J Brodersen, F Bruneault, ... Frontiers in Human Dynamics 3, 688152, 2021 | 37* | 2021 |
| Human-like intuitive behavior and reasoning biases emerged in large language models but disappeared in ChatGPT T Hagendorff, S Fabi, M Kosinski Nature Computational Science 3 (10), 833-838, 2023 | 36* | 2023 |
| Privacy Literacy and Its Problems. T Hagendorff Journal of Information Ethics 27 (2), 2018 | 36 | 2018 |
| Machine intuition: Uncovering human-like intuitive decision-making in GPT-3.5 T Hagendorff, S Fabi, M Kosinski arXiv preprint arXiv:2212.05206, 2022 | 32 | 2022 |
| On assessing trustworthy AI in healthcare. Machine learning as a supportive tool to recognize cardiac arrest in emergency calls RV Zicari, J Brusseau, SN Blomberg, HC Christensen, M Coffee, ... Frontiers in Human Dynamics 3, 673104, 2021 | 29 | 2021 |
| From Principles to Practice. An interdisciplinary framework to operationalise AI ethics. L Fetic, T Fleischer, P Grünke, T Hagendorf, S Hallensleben, M Hauer, ... | 29 | 2020 |
| Linking human and machine behavior: A new approach to evaluate training data quality for beneficial machine learning T Hagendorff Minds and Machines 31 (4), 563-593, 2021 | 27* | 2021 |
| From Principles to Practice-An interdisciplinary framework to operationalise AI ethics T Krafft, M Hauer, L Fetic, A Kaminski, M Puntschuh, P Otto, C Hubig, ... iRights. Lab, Tech. Rep., 2020 | 26 | 2020 |
| Ethical considerations and statistical analysis of industry involvement in machine learning research T Hagendorff, K Meding Ai & Society, 1-11, 2023 | 25* | 2023 |
| Speciesist bias in AI: how AI applications perpetuate discrimination and unfair outcomes against animals T Hagendorff, LN Bossert, YF Tse, P Singer AI and Ethics 3 (3), 717-734, 2023 | 24 | 2023 |
| Machine Learning and Discrimination: Problems and Solutions T Hagendorff Österreichische Zeitschrift für Soziologie 44, 53-66, 2019 | 23* | 2019 |
| AI, governance and ethics: global perspectives A Daly, T Hagendorff, H Li, M Mann, V Marda, B Wagner, WW Wang University of Hong Kong Faculty of Law Research Paper, 2020 | 22 | 2020 |
| Das Ende der Informationskontrolle T Hagendorff Digitale Mediennutzung jenseits von Privatheit und Datenschutz, 2017 | 22 | 2017 |
