Animating AI and Information Literacy: Visualizing Research from NU London's Computational Philosophy Lab

Visualizing AI & Information Literacy Research at the Computational Philosophy Lab

Data and theory visualizations, including animations, offer a clear and engaging way to present academic research that might otherwise seem dry. This initiative focuses on creating new methods to communicate key findings from AI and Information Literacy research at the Computational Philosophy Lab (CPL) at Northeastern University London.

The CPL conducts research in areas such as information sharing through computer simulations, automated proof construction for scientific discovery and education, and mapping AI ethics through co-authorship and citation network analysis. Key projects include PolyGraphs (information sharing simulations), Consilient Reasoning (automating proofs), and the Network Analysis of the AI Ethics Field.

About the Computational Philosophy Lab

The CPL is the UK’s first dedicated academic unit for computationally-enabled and AI-enhanced philosophy. It acts as a hub in London connecting the broader Northeastern University network with European partners. The lab supports collaborations that produce research relevant to academics, policymakers, practitioners, and civil society.

The lab’s four main research areas are:

• AI Ethics
• AI Creativity
• AI & Information Literacy
• Philosophical Simulations

Project Team

• Principal Investigator: Prof Ioannis Votsis
• Co-Principal Investigators: Prof Brian Ball, Dr David Freeborn, Dr Alice Helliwell

Recent Publications

• Ball, B., Koliousis, A. (2023). Training philosopher engineers for better AI. AI & Society 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. Humanities and Social Sciences Communications 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. Humanities and Social Sciences Communications 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. (2024). Aesthetic Value and the AI Alignment Problem. Philosophy & Technology 37, 129. https://doi.org/10.1007/s13347-024-00816-x
• Helliwell, A.C. (2021). Darwinian creativity as a model for computational creativity. 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. https://doi.org/10.1017/psa.2025.1
• Votsis, I. (2025). Grounded Empiricism. European Journal for Philosophy of Science. 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.

The CPL’s work is a valuable resource for those interested in the intersections of AI, philosophy, and information science. For professionals seeking to deepen their expertise in AI applications and ethics, exploring dedicated AI courses can be beneficial. Explore relevant offerings at Complete AI Training.