Aug 2026· Artificial Intelligence & Environment· 0 citations· 6 references
TL;DR
This editorial traces key technological milestones across seven decades, from early symbolic reasoning to today's agentic systems capable of autonomously generating hypotheses and accelerating discovery, and examines promising future directions.
Abstract
The 70th anniversary of the 1956 Dartmouth Summer Research Project offers an occasion to celebrate artificial intelligence's extraordinary trajectory from a bold hypothesis about machine simulation of intelligence to a transformative force reshaping science, medicine, and environmental stewardship. This editorial traces key technological milestones across seven decades, from early symbolic reasoning to today's agentic systems capable of autonomously generating hypotheses and accelerating discovery. It then examines promising future directions, with particular emphasis on AI's rapidly expanding role in scientific research from protein structure prediction to AI co-scientists that collaborate with researchers in real time. Far from a source of apprehension, AI stands as one of the most powerful tools ever devised for expanding the frontiers of human knowledge, provided we guide its development with wisdom, responsibility, and a steadfast commitment to human flourishing.
The advancement of AI in science raises broader questions concerning the division of cognitive labour between human researchers and machines, and a typology of AI systems used in research is proposed, ranging from specialised scientific AI through scientific AI assistants and agents to hybrid experimental systems that...
P. Jedlička· Teorie vědy / Theory of Scie...· 0 citations
In 2026, three landmark Nature papers collectively announced that artificial intelligence has crossed a threshold, moving from a laboratory instrument to an autonomous research agent. The Empirical Research Assistant (ERA) writes expert-level scientific software across multiple domains. The AI Scientist executes the en...
This article examines the emerging paradigm of agentic AI for scientific discovery, traces the conceptual shift from tools to agents, lays out a six-stage workflow spanning literature synthesis to manuscript generation, and reviews practical systems in chemistry, equation discovery, materials science, and general machi...
Alexander Taktakidze· Longevity Horizon· 1 citation
A survey of the past and future of AI Scientists: machines capable of automating science, which have the potential to transform science and create a new form of science that will create a new form of science and transform the world.
Digital computers have reshaped scientific practice, moving working scientific knowledge from printed texts into algorithms, simulations, and models. Advances in artificial intelligence (AI) are now accelerating that shift, progressing science in areas from protein folding to climate modelling, and raising the prospe...
Kyle Cranmer, Neil D. Lawrence, Jessica K Montgomery et al.· Robotics: Science and System...· 0 citations
Overall, it is found that the use of coding agents in scientific computing holds great promise for accelerating scientific research and increasing the reliability of critical systems, but that outstanding concerns remain.
Jeremiah H. Li, Alex Rubinsteyn, Sergey Feldman et al.· bioRxiv· 0 citations
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