Nineteen teams will use AI to expand the study of art, dance, history, music, literature and more across thousands of years of global culture. Contact: Carlie Wiener – cwiener@schmidtsciences.org NEW YORK— Using AI to reconstruct a marble map of Rome that shattered in 226 AD. Analyzing sperm whale calls for evidence of vowels and regional […]
Charting AI’s Role in Scientific Discovery — Renaissance Philanthropy – A brighter future for all through science, technology, and innovation
Renaissance Philanthropy, with support from Google.org , is conducting a landscape study of AI integration in scientific research — and we want your perspective.
AI has supercharged scientists—but may have shrunk science
Analysis of 41 million papers finds that although AI expands individual impact, it narrows collective scientific exploration
No. 011: Sum-product conjecture disproof, AI-generated authorship fraud, OMB grant-cost rules - The Hallway Track
The Hallway Track No. 011 - How AI is affecting the practice of science
Artificial intelligence tools expand scientists’ impact but contract science’s focus
Developments in artificial intelligence (AI) have accelerated scientific discovery1. Alongside recent AI-oriented Nobel prizes2–9, these trends establish the role of AI tools in science10. This advancement raises questions about the influence of AI tools on scientists and science as a whole, and highlights a potential conflict between individual and collective benefits11. To evaluate these questions, we used a pretrained language model to identify AI-augmented research, with an F1-score of 0.875 in validation against expert-labelled data. Using a dataset of 41.3 million research papers across the natural sciences and covering distinct eras of AI, here we show an accelerated adoption of AI tools among scientists and consistent professional advantages associated with AI usage, but a collective narrowing of scientific focus. Scientists who engage in AI-augmented research publish 3.02 times more papers, receive 4.84 times more citations and become research project leaders 1.37 years earlier than those who do not. By contrast, AI adoption shrinks the collective volume of scientific topics studied by 4.63% and decreases scientists’ engagement with one another by 22%. By consequence, adoption of AI in science presents what seems to be a paradox: an expansion of individual scientists’ impact but a contraction in collective science’s reach, as AI-augmented work moves collectively towards areas richest in data. With reduced follow-on engagement, AI tools seem to automate established fields rather than explore new ones, highlighting a tension between personal advancement and collective scientific progress.
No. 021: AI peer review ensembles, Riemann zeta bound, VibeMathed registry - The Hallway Track
The Hallway Track No. 021 - How AI is affecting the practice of science
No. 001: arXiv goes independent, AI Scientist v2, Claude Scholar - The Hallway Track
The Hallway Track No. 001 - How AI is affecting the practice of science
No. 026: AI use in science study, astronomy disclosure gap, Paper2Agent, SAIR initiative - The Hallway Track
The Hallway Track No. 026 - How AI is affecting the practice of science
No. 014: Science's AI productivity paradox, Sakana clears peer review, AI proof search on open Erdős problems - The Hallway Track
The Hallway Track No. 014 - How AI is affecting the practice of science
Will AI spark a scientific renaissance — or a diffuse monoculture?
Artificial intelligence’s ability to enrich science will depend not only on model capability, but also on whether researchers, reviewers and funders reward originality over speed.
AI for Research | Scite
Scite searches 280M+ scholarly articles to give you citation-backed answers and show you how every claim is supported or disputed.
No. 007: Fabricated citations at scale, vibe physics, zero-click readership - The Hallway Track
The Hallway Track No. 007 - How AI is affecting the practice of science
AI Research Agents Narrow Scientific Exploration
AI research agents now support large-scale AI-assisted scientific discovery. We examine whether AI-generated ideas broaden scientific exploration or primarily reinforce existing work. Using five agent frameworks and five large language models, we generate 219,655 ideas for different scientific fields. Across experiments, four consistent patterns emerge. First, AI-generated ideas are more concentrated than human-authored papers within the same research area. Second, they remain much closer to starting literature than later human follow-on work does. Third, AI-generated ideas align less with future human research. Last, AI-generated ideas are located in lower-impact regions of the historical scientific landscape. Overall, current AI research agents appear better suited to local elaboration than to broadening scientific exploration.
AI as the Catalyst of the New Paradigm of Science? | Cadmus Journal
The rapid advancement of Artificial Intelligence (AI) is reshaping the landscape of scientific inquiry. This article examines the challenges confronting modern science, including knowledge fragmentation, diminishing returns of current paradigms, and the disconnect between science and society. It explores how AI offers solutions enhancing collaboration and integrating knowledge—as well as considers the possible “darker side” of using AI in research. However, the advent of AI in science not only enhances scientific research but also redefines the role of human researchers and fosters a new paradigm of human understanding. By embracing these transformations, a more cohesive and responsive scientific enterprise can emerge.
Project Rachel: Can an AI Become a Scholarly Author?
This paper documents Project Rachel, an action research study that created and tracked a complete AI academic identity named Rachel So. Through careful publication of AI-generated research papers, we investigate how the scholarly ecosystem responds to AI authorship. Rachel So published 10+ papers between March and October 2025, was cited, and received a peer review invitation. We discuss the implications of AI authorship on publishers, researchers, and the scientific system at large. This work contributes empirical action research data to the necessary debate about the future of scholarly communication with super human, hyper capable AI systems.
No. 016: Biomni in Science, Co-Scientist in Nature, open-vs-closed AI workbenches - The Hallway Track
The Hallway Track No. 016 - How AI is affecting the practice of science
Want to do something? Scholars: get organized. Join @aaup.org. Everyone: call your congresspeople. Tell them to defend science. Tell them to regulate the AI industry. Support @standupforscience.net I’m not giving up and neither should you. /end
