The Donders Centre for Cognition is looking for a PhD candidate in Computational Cognitive Science to work on a meta-theoretical research project spanning cognitive science and artificial intelligence (AI). Are you excited to advance our scientific understanding of what a cognitive capacity is? Do you question the AI hype on the so-called human-like capacities of machines? Do you enjoy thinking deeply and critically? If so, this position may be for you. In this PhD project, titled ’Cognitive capacities and machines: Why do calculators exist, if AGI cannot?’, you will adopt various theoretical and meta-theoretical methodologies (including literature review, conceptual engineering and formal analysis) to study and characterise: 1. What are cognitive capacities? 2. What kinds of cognitive capacities, if any, can exist in sociotechnical artefacts and/or is there always a human in the loop? 3. And which epistemologies provide a way out of the conundrum of hyperempiricism, such that we can have a sound and coherent science of cognitive capacities?
We are living in a time of AI hype. Many believe that artificial general intelligence (AGI) is around the corner, and that we already have systems with genuinely human-like cognitive capacities (
van Rooij, Guest, et al., 2023). However, exactly what cognitive capacities are is never formally or coherently pinned down, leaving AI vulnerable to hype. Using conceptual, formal, historical, and meta-theoretic analyses, this project aims to build a protective belt.
A small part of the position (0.1FTE) will involve contributions to education, for example in the form of thesis supervision and teaching assistantships for courses (such as
AI as a Science,
Theoretical Modelling for Cognitive Science).
Other relevant work by the team:
- Guest, O. (2024). What makes a good theory, and how do we make a theory good? Computational Brain & Behavior.
- Guest, O., & Martin, A. E. (2021). How computational modeling can force theory building in psychological science. Perspectives on Psychological Science. 16(4), 789–802.
- Guest, O., & Martin, A. E. (2023). On logical inference over brains, behaviour, and artificial neural networks. Computational Brain & Behavior,6(2), 213–227.
- van Rooij, I., Guest, O., Adolfi, F. G., de Haan, R., Kolokolova, A., & Rich, P. (2023). Reclaiming AI as a theoretical tool for cognitive science. PsyArXiv.
- Blokpoel, M., & van Rooij, I. (2021). Theoretical modeling for cognitive science and psychology.
- Blokpoel, M. (2018). Sculpting computational-level models. Topics in cognitive science, 10(3), 641–648.