Petr O. Jedlicka | Searcharxiv

arXiv2026

Quo Vadis? Scientific Discovery in the Age of Artificial Intelligence

This paper examines the growing role of AI in scientific discovery. It first surveys the rapid rise of AI capabilities, especially in reasoning, abstraction, planning, and long-horizon task execution, before turning to scientometric evidence of AI's diffusion across the sciences. It then proposes a typology of AI systems used in research, ranging from specialized scientific AI through scientific AI assistants and agents to hybrid experimental systems that combine computation and physical experimentation. On this basis, it offers a selective overview of recent achievements in mathematics and computer science, physics, chemistry, the life sciences, and the behavioural and social sciences. It argues that, despite these advances, current systems remain constrained by important technical, epistemic, and institutional limitations, and that their growing use introduces both near-term and longer-term risks. The conclusion further suggests that the advancement of AI in science raises broader questions concerning the division of cognitive labour between human researchers and machines.

cs.CY↗

arXiv2026

Why do we need social singularity? A mechanism-based critique of gradual scenarios in AI existential-risk discourse

This paper critiques recent gradual and cumulative AI existential-risk scenarios, arguing that, despite their substantive contributions, they remain insufficiently sociologically specified. In particular, these scenarios lack a reflexive perspective, retain a largely technologically deterministic structure, and underestimate the role of collective agency and other social processes. As a result, they also discount the possibility of major social conflict accompanying AI diffusion, which limits their overall plausibility. The paper further identifies a set of social mechanisms likely to become significant before or during AI deployment, including interpretive and performative dynamics, mobilisation and countermobilisation, path dependence and lock-in, cross-regime divergence and multi-speed diffusion, and social-psychological mechanisms such as attachment and reactance. It argues that these mechanisms will interact recursively with AI diffusion and reshape future trajectories, which may subsequently branch, reverse, or undergo discontinuous shifts, thereby expanding the space of plausible AI futures. On this basis, the paper also proposes a novel analytic distinction between technological singularity and social singularity. Whereas the former refers to a putative technological threshold in AI development, the latter denotes a social discontinuity produced by the anticipated approach of that threshold. The central implication is that the most consequential disruptions may emerge not only from advanced AI itself, but also from the social dynamics provoked by the expectation of its arrival.

cs.CY↗