Ethics and Epistemology of AI in Science: Studies of Machine Learning Poverty Prediction
Project dates:
Sep 2021 – June 2025
Name of the PhD student
Alexander Martin Mussgnug
Supervisors:
Shannon Vallor – School of Philosophy, Psychology and Language Sciences (Philosophy)
Arno Onken – School of Informatics (Data Science for Life Sciences)
Sabina Leonelli – University of Exeter, School of Sociology, Philosophy and Anthropology
Project aims:
This project lies at the intersection of philosophy of science and AI ethics, where Alexander examines how AI applications can be both epistemically reliable and ethically beneficial. This work highlights the importance of understanding AI within the context of established practices, recognizing the cultivated wisdom and accumulated experience they represent.
Disciplines and subfields engaged:
AI Ethics
Philosophy of Science
Supervised Machine Learning
Research Themes:
Ethics of Algorithms
Algorithmic Transparency and Explainability
Ethics of Human-Machine Interactions
Ethics of Knowledge Augmentation
Ethics and Politics of Data
Ethics of Data Science and Data Practice
Emerging Technology and Human Identity
AI, Automation and Human Wisdom
Related outputs:
Technology as Uncharted Territory: Integrative AI Ethics as a Response to the Notion of AI as New Moral Ground, Alexander Martin Mussgnug, Philos. Technol. 38, 106 (2025). 🔗
Presented on the relationship between AI ethics and the philosophy of science on the Mobilising Technomoral Knowledge panel at the Society for Philosophy & Technology Conference 2023 in Toyko.
Presented on the use of operational definitions in machine learning at the British Society for the Philosophy of Science Annual Meeting 2023 and at the Workshop “Measuring the Human: New developments in the epistemology of measurement in the human sciences”
Delivered an invited talk on the relationship between AI and conceptual freedom at the workshop AI and the Christian Churches, 2023.
The predictive reframing of machine learning applications: good predictions and bad measurements, Alexander Martin Mussgnug, European Journal for Philosophy and Science 12(3), 2022 🔗