Carina Prunkl

Dr Carina Prunkl is a Research Fellow at the Institute for Ethics in AI and an affiliate of the Centre for the Governance of AI at the Future of Humanity Institute. She works on the ethics and governance of AI with a focus on human autonomy, the ethics of autonomous systems, and responsible research and innovation. Dr Prunkl interacts with policy leaders across the globe to help develop solutions to current AI governance issues. At Oxford, she is currently teaching the class on Governance of AI for the EPSRC Centre for Doctoral Training in Autonomous and Intelligent Machines and Systems.

She holds a BSc and MSc in Physics from Freie Universität Berlin, an MSt in Philosophy of Physics and a DPhil in Philosophy from the University of Oxford. She previously worked as a Senior Research Scholar at the Future of Humanity Institute.

  • Milano, S., and Prunkl, C. "Epistemic Injustice and Algorithmic Profiling". In Philosophical Studies, special issue on Normative Theory and AI, eds. Lazar, S. et al. Prunkl, C. Forthcoming.
  • Mazijn, C., Prunkl, C., Algaba, A., Danckaert, J., & Ginis, V. "LUCID: Exposing Algorithmic Bias through Inverse Design". In AAAI Conference Proceedings 2023. Forthcoming
  • Robertson, K., and Prunkl, C., (forthcoming). How objective is thermodynamics? In Philosophy of Science 
  • Prunkl, C., Is there a trade-off between human autonomy and the 'autonomy' of AI systems? Philosophy and Theory of Artificial Intelligence 2021, ed. V. Müller, Springer Cham, 2022
  • Prunkl, C., Human Autonomy and Artificial Intelligence. In Nature Machine Intelligence 4: 99-101, eds. Chang, R., and Srinivasan, A., Oxford University Press. 2022
  • Prunkl, C., Ashurst, C., Anderljung, M., Webb, H., Leike, J., Dafoe, A., Institutionalising Ethics in AI through Broader Impact Requirements Nature Machine Intelligence 3:104–110, 2021
  • Veliz, C., Prunkl, C., Phillips-Brown, M., and Lechterman, T. M. (2021). "We Might Be Afraid of Black-Box Algorithms". In Journal of Medical Ethics 47.5: 339-340 (2021)
  • Brundage, M., et al. Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims, Report, 2020
  • Prunkl, C., and Whittlestone J., Beyond near and far: A new taxonomy for the AI Policy space Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 138-143, 2020