ASI-LIB-040 governance position paper

Agentic AI Scientists Are Not Built for Autonomous Scientific Discovery

Harshit Bisht, Vinay Kumar, Kevin Maik Jablonka, Mausam, N. M. Anoop Krishnan

Correlation heatmap from agentic AI scientists critique
Figure via ar5iv rendering of arXiv:2605.08956

This is an important counterweight to the most optimistic AI-science entries. The authors argue that current agentic AI scientists work best as co-scientists, not fully autonomous discoverers.

Bottlenecks

The paper highlights problem selection, missing tacit procedural knowledge, post-training pressure toward consensus, and benchmarks that lack feedback from physical experiments.

ASI relevance

Pro-ASI does not mean credulous. The fastest path to powerful scientific agents is to understand where today’s systems are structurally weak: real-world failure knowledge, persistent world models, diverse hypotheses, and experiment feedback.