Partially supported by a NULab Seedling Grant.
Data and theory visualizations (including animations) are extremely powerful in communicating otherwise dry academic research. This project seeks to develop novel ways of communicating key findings emerging from AI & Information Literacy research currently being conducted under the auspices of Computational Philosophy Lab (CPL) at NU London. This includes research in information sharing via computer simulations (project: PolyGraphs), automating proof construction for the purposes of scientific discovery and education (project: Consilient Reasoning), and mapping AI ethics co-authorship and citation networks (project: Network Analysis of the AI Ethics Field).
The CPL is the UK’s first and premier academic research unit for computationally-enabled and AI-enhanced philosophy. Serving as a London hub for related work within the broader Northeastern University network, and acting as an institutional bridge to Europe, the CPL fosters collaborations with partners to deliver impactful research for academics, policymakers, practitioners, and civil society. Its four main areas of research are: AI Ethics, AI Creativity, AI & Information Literacy and Philosophical Simulations.
To learn more, visit the Computational Philosophy Lab’s website.
Project Team:
- Principal Investigator: Prof Ioannis Votsis
- Co-PIs:
Publications:
Ball, B., Koliousis, A. (2023) Training philosopher engineers for better AI. AI & Soc 38, 861–868. https://doi.org/10.1007/s00146-022-01535-7
Ball, B., Koliousis, A., Mohanan, A. et al. (2024a) Misinformation and higher-order evidence. Humanit Soc Sci Commun 11, 1294. https://doi.org/10.1057/s41599-024-03806-8
Ball, B., Koliousis, A., Mohanan, A. et al. (2024b) Computational philosophy: reflections on the PolyGraphs project. Humanit Soc Sci Commun 11, 186. https://doi.org/10.1057/s41599-024-02619-z
Freeborn, D.P.W. (2024) Rational factionalization for agents with probabilistically related beliefs. Synthese 203, 46. https://doi.org/10.1007/s11229-024-04491-5
Freeborn, D.P.W. (2025) Effective theory building and manifold learning. Synthese 205, 23. https://doi.org/10.1007/s11229-024-04844-0
Helliwell, A.C. (forthcoming), Creativity, Agency, and AI. In Philosophy of AI the State of the Art, Vincent C. Müller, Leonard Dung, Guido Löhr & Aliya Rumana (eds.)., Berlin: Springer Nature.
Helliwell, A.C. Aesthetic Value and the AI Alignment Problem. Philos. Technol. 37, 129 (2024). https://doi.org/10.1007/s13347-024-00816-x
Helliwell, A.C. (2021), Darwinian creativity as a model for computational creativity. In Proceedings of the 7th Computational Creativity Symposium at AISB 2021 (pp. 15-19). The Society for the study of Artificial Intelligence and Simulation of Behaviour.
O’Connor C, Freeborn D.P.W. (2025) Industrial Distraction. Philosophy of Science. Published online 1-22. doi:10.1017/psa.2025.1
Votsis, I. (2025) ‘Grounded Empiricism’, European Journal for Philosophy of Science, DOI: https://doi.org/10.1007/s13194-025-00644-6.
Votsis, I. (2024a) ‘Modelling Analogical Reasoning: One-Size-Fits-All?’, in B. Ball, A. Helliwell, and A. Rossi (eds.), Wittgenstein and AI (Vol. I), London: Anthem Press.
Votsis, I. (2024b) ‘A Neuro-Symbolic Approach to the Logic of Scientific Discovery’ in E. Ippoliti, L. Magnani, and S. Arfini (eds.), Model-Based Reasoning, Abductive Cognition, Creativity, Studies in Applied Philosophy, Epistemology and Rational Ethics, vol. 70, Springer.
