Seminar series

AI research evolves as a network of interacting ideas, communities, and technologies. Using phylo-epistemic networks, the talk explores the history of modelling language as a complex adaptive system. This case study highlights how alternative research trajectories can live, raising important questions about the diversity and future directions of AI research.

From the democratization of dual-use biotechnology to the emergence of deceptive agentic systems, the trajectory of Artificial Intelligence raises urgent questions about control and alignment. In this talk, Charbel-Raphaël Segerie presents a critical analysis of the current race toward superintelligence and the widening gap between technological capabilities and control mechanisms.

In this talk, Pierre Bessière presents the central ideas of his new book: why having a body fundamentally shapes intelligence, why disembodied AI systems depend on humans for meaning, and how natural agents remain necessarily ignorant of the world they act in. He contrasts two models of reasoning: logic and probability, arguing that only probabilistic reasoning allows intelligences to act meaningfully under uncertainty.

Dominique Lestel explores humanoid robots like Sophia as “Insurrectionary Machines” — artifacts that unsettle rather than serve, existing in friction with humans. From ancient idols to AI systems, these machines invite us to rethink life itself through an ethological lens.

Kathinka Evers explores why the question of artificial sentience (or “awareness”, or “consciousness”) is raised in science receiving considerable public funding despite the lack of empirical evidence? What this might mean and what the implications of it are.

Are qualitative differences in conscious experience, like vision versus audition, shaped by the intrinsic structure of neural networks? This talk proposes a mathematical framework using symmetry groups and equivariance to characterize these differences. This approach offers a new path for linking consciousness to neural architecture.

Can traditional notions of consent meaningfully apply to AI-generated content? What happens when our data creates representations of ourselves beyond our control?

How can we ensure AI systems' alignment with human values?