Silvia Milano is Akademische Rätin at the Technical University of Munich, within the Chair of Philosophy and History of Science and Technology, and Head of Research of the Ethical Data Initiative at TUM Think Tank.
Her research examines how algorithmic systems — particularly recommender systems and AI assistants — shape knowledge, values, and rational agency, and develops frameworks for evaluating and governing their effects. She draws on formal and social epistemology, applied ethics, and political philosophy to build theoretically rigorous accounts with implications for policy and design.
Before joining TUM, she was Senior Lecturer in Philosophy at the University of Exeter and a Humboldt Fellow at the Munich Centre for Mathematical Philosophy (LMU Munich). Prior to that, she was a Research Fellow at the Future of Humanity Institute and William Golding Junior Research Fellow in Philosophy at Brasenose College, University of Oxford. She completed her PhD in Philosophy at the London School of Economics and Political Science in 2018.
- Ethics and epistemology of recommender systems and algorithmic profiling
- AI and epistemic justice: polarisation, hermeneutical injustice, and algorithmic mediation of knowledge
- Rational agency and AI: how AI systems reshape individual decision-making and autonomy
- Governance and regulation of data and algorithmic systems
- Formal epistemology: Bayesian approaches to self-locating belief and rational updating under uncertainty
More info at: https://silvia-milano.com/research/
- Milano, S. and C. Prunkl. 'Algorithmic profiling as a source of hermeneutical injustice.' Philosophical Studies, 182(1), 185–203 (2025).
- Milano, S. and S. Nyholm. 'Advanced AI assistants that act on our behalf may not be ethically or legally feasible.' Nature Machine Intelligence, 6(8), 846–847 (2024).
- Milano, S. and A. Perea. 'Rational Updating at the Crossroads.' Economics and Philosophy, 40(1), 190–211 (2024).
- Milano, S. 'Recommended!' In David Edmonds (ed.), Living with AI: Moral Challenges. Oxford University Press (2024).
- Milano, S., McGrane, J., and Leonelli, S. 'Large language models challenge the future of higher education.' Nature Machine Intelligence (2023).
- Milano, S., Mittelstadt, B., Wachter, S., and Russell, C. 'Epistemic fragmentation poses a threat to the governance of online targeting.' Nature Machine Intelligence, 3, 466–472 (2021).
- Milano, S., Taddeo, M., and Floridi, L. 'Recommender Systems and their Ethical Challenges.' AI & Society, 35, 957–967 (2020).
Full list: https://silvia-milano.com/cv/
TUM (current): Philosophy of Information (Masters); Social Epistemology (Masters); Philosophy of Decision Making Systems (Masters).
Teaching qualifications: ASPIRE Fellowship and PGCertHE, UK Higher Education Academy (2024).
- Ethics of AI and algorithmic systems
- Philosophy of technology
- Epistemology (formal and social)
- Data governance and regulation
- Recommender systems
- Decision theory and rational choice
- [Keynote] 'Borrowed Wisdom: AI-assisted learning and the temptation of easy knowledge,' EUonAIR Symposium on the Ethics of Generative AI in Education and Research, Lugano, June 2026.
- 'Recommender Systems and Epistemic Polarisation,' BSPS Annual Conference, Glasgow, July 2025.
- [Keynote] 'Accuracy of Prediction and Freedom of Choice,' GWP Congress on Philosophy of Science, Erlangen, March 2025.
- 'Rational Updating at the Crossroads,' Carnegie Mellon Philosophy Colloquium, April 2023; First Paris Conference: Frontiers of Philosophy and Economics, May 2024.
- [Keynote] 'Fair for whom? Towards an overarching account of fairness in recommendation,' Recommender Systems: Legal and Ethical Issues, Bonn, December 2021.
Full list: https://silvia-milano.com/news/#talks
Referee for: AI & Society; Analysis; British Journal for the Philosophy of Science; Dialectica; Erkenntnis; Mind; Minds and Machines; Nature Machine Intelligence; Noûs; Philosophical Quarterly; Philosophy & Technology; Synthese.
Program committee: AIES 2021; ACM FAccT 2022; TARK 2021 and 2023.
- Humboldt Fellowship for Experienced Researchers (2023–2025), Alexander von Humboldt Foundation. Fully funded 18-month research stay at the MCMP, LMU Munich.
- Popper Prize (2017/18), LSE Department of Philosophy, for 'Bayesian Beauty'.
AHRC PhD Scholarship (2013–2016), Managing Severe Uncertainty Project, LSE.