Hannah Clausen

简介

Hannah has a bachelor's degree in Political Science and Sociology from the University of Göttingen and a master's degree in Social Data Science from the University of Copenhagen. During her studies, she focused on the quantitative analysis of social media data as well as gender bias in LLMs. Moreover, Hannah worked in multiple research projects within sociology, diversity research, and gender studies particularly focusing on research methodology. PhD project Benchmarking Ethical Reasoning in Large Language Models The project combines NLP and philosophy aiming at developing a benchmarking methodology for machine ethics in LLMs. A particular focus lies on the evaluation of moral judgments by LLMs.

代表成果

• Scientific articles and book chapters
• Clausen, Hannah; Kutuzov, Andrey; Smajdor, Anna & Velldal, Erik (2026). Assessing Moral Judgment by Large Language Models – A Survey of Available Datasets. Northern European Journal of Language Technology (NEJLT). ISSN 2000-1533. 12(1), p. 88–116. doi: 10.3384/nejlt.2000-1533.2026.6366. Full text in Research Archive Show summary Recent advances in language modeling have contributed to a growing emphasis on machine ethics, including researching and assessing moral judgments made by large language models (LLMs). This paper provides a critical survey of the existing datasets for exactly this assessment, with a special focus on the respective data sources. We address the current lack of theoretical grounding by providing an introduction to ethics and different frameworks from moral philosophy and moral psychology. Moreover, we identify four main data sources: webcrawled corpora, scholars, laypeople, and synthetic data generation. By discussing the strengths and weaknesses of these sources, we analyze their implications for the assessment of moral judgment. Importantly, systemizing the available datasets reveals an over-reliance on previous work, reinforcing existing shortcomings. Addressing the current limitations, we recommend adopting a consistent terminology and creating independently curated datasets based on interdisciplinary work. To ensure a clear delineation of normative approaches, we propose focusing on the assessment of moral consistency and certainty of LLMs as effective and well-defined indicators of their performance on moral judgment.
• Clausen, Hannah (2025). Ethical Issues in the Use of Surveys on LLMs. Full text in Research Archive
• Clausen, Hannah; Kutuzov, Andrey; Smajdor, Anna & Velldal, Erik (2025). Assessing Morality in Large Language Models - A Survey. Full text in Research Archive Show summary Poster Presentation of the current state of research presenting datasets, approaches and theories used to evaluate moral judgment by large language models
• Clausen, Hannah (2025). Benchmarking Ethical Reasoning in Large Language Models - Visit of the Scientific Advisory Committee. Full text in Research Archive Show summary Project presentation for the Scientific Advisory Committee (SAC) discussing the state of research, relevant shortcomings therein and how to address these
• Clausen, Hannah (2024). Benchmarking Ethical Reasoning in Large Language Models - Integreat Annual Retreat 2024. Full text in Research Archive