In the recently published preadrint named The potential of the AI researchers in discoveries of science: missing things?Hengjie researchers and yaochu jin from Westlake University And Westlake Institute for advanced education for advanced education in Hangzhou, ChinaShine about artificial intellectual evolution in scientific research. Released in March 2025, education provides detailed analysis of AI has increased influence in high-impact scientific journal And that means the demand of better AI researchers in the scientific discovery process.
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AI of scientific research
Studies show Important research in the AI-DREIME in the last decadeEspecially within a famous Natural Index Journal, collective with 145 high effects are selected for their reputation. According to the author of the author 20,401 Ai-tight associated with Web site collection of scientific coursesThe occurrence of AI in these magazines rose Nine since 2015. In 2024, the writing associated with AI calculated for 3.57% of the total magazine while the article is young.
This growth is due to the breakdown of machine learning and large language models (llms), which change fields Biology, Chemistry, Chemistry, and Resume. Note examples include Imphone and EsmfoldWhich has redeemed Protected protein structureAnd a tool that looks like gpttolltype and PATHCHAWhich Apreline ORderiation of cells and Diagnosis PathologyRespectively. Despite the progress, the author note it is a small component of the overall scientific output, suggesting that its full potential has not yet known.
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AI’s future estimate in science
Drawing Distribution of invention theory-A framework that new technology has been forced to researchers – Researchers Project A great deal of increasing In the role of AI to Discover Science Over a decade to come. Theory, developed by Everett RogersIndicates that adoption to compliance Picture curve sStart with the inventors and adopters early before spreading to a wide population. Use this mode, Yu and Jin and Jin and Jin and Jin 25% of all publications in natural Index magazineUp from now 3.57%. This estimate is to continue developing an ongoing AI tools and researchers participation in scientific efforts.
Authors runs that while the fields are preferred Computer Biology and Material Sciences The AI Early, a vast breasts throughout other discipline will make this growth. However, they are careful that the pace This growth may slow down while Ai ripen And become a standard tool in research, with natural tissue seen in the previous transformation technology Selecting a computer model and high connection settings.
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Who leads the responsibility?
The uncommon discovery from the study is The domination of the experimental scientist In ai-drime research. 80,945 authors who are authors who come from the writer associated with AI related to the year of 20,401 shows that Nearly 90% of this work is led by researchers from a scientific institutions Instead of those who focus on AI. While the participation of the AI institution has grown in 14.41% of documents in 2015 to 1924 percent of their functions remain supported. The ratio of documents led by the AI institution, where they are first stated, each year, with their majority rankings at approximately 1.1.
This greater trend in five famous magazinesCharacteristics, character communication, science, processing, scientific and The proceedings of the National Assembly of Science (PNAS)AI researchers are active but still rarely leader. In 2024, the AI Institute contributes 40% of the articles in these magazines, only 14.6% known as relationships for the first time. Researchers have suggested that this unbalance reflects the difficulties to discover the scientific scientific discovery, which they intended to solve strategic problems.
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Strategies to strengthen AI researchers
To unlock the full capacity of AI, the authors offer Three important directions. First, they supported for Development AI Friendly Tools with Appropriate Users for Test Scientists. The tool, which can be done Automatic data analysis, modeling, and design trialIt is already used by early adopters and can extend the effects of AI if easily accessible. For example, SHAP (shaple readitive retinations has adopted widely in effective discipline and science.
Secondly, the author calls for researchers AI play a role more strict than scientific discovery by Bridging a consignment gap and how. Currently, only about 8% of the AI research led by AI, figures in the previous year. Studying this feature on the lack of understanding about the AI can be used and how the AI researchers can guide. To solve this problem, they recommend focusing on the fields An existing data package or with no potential potentialLike that File design and weather forecastAnd and develop Expert algorithm To solve these problems.
Third, researchers emphasized the requirements of ai-driverden ecology. This is related to the combination, Establishment of standards for using AIAnd creating an invention platform. Tool success as Shap, accommodated by accessible software packages, show that way Ecological system Can speed up progress. By Ancient explanation in an increase in performance performance performanceAI researchers can provide understanding that reflects the Scientific Goal, AI Investment In the Research Process.
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Methods of practical and stream
Study Cart Four course of practical To equip a pilot scientist to AI: User analysis platform, llms with domain updates for rare situations of data, automatic data test system. These methods aim the barriers that make AI adopt AI while offering a chance to researchers ai. For example, advanced mistsimodal llms can stimulate the extraction of textured data from unrealized scientific articles, with no effective promises.
In addition, the authors offer ai4cience ai4cience ai4cience workflow for AI researchers, pushing them Define science problems, help with existing information or literary of literacy, and collaborate with the laboratory laboratory for accuracy. This way, they argue, the AI researchers while the most important provider than a major change provider of AI potential.
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The challenge and future predictions
When there is optimistic, the study recognized difficulties such as AI “deviation” – anywhere Create false results– and human monitoring requirements in science reasons. Experimental examination, author’s pressure, is also necessary to ensure strict, especially to discover Ai-Driven extended. They also noticed that the pressure is facing the Researcher AI, by saying a quote from Kyunghyun Cho: “I feel anxious and frustration that neurips’24“Reflection of a strong landscape that they navigate the way.
In conclusion, the work of Yu and Jin is emphasized while Ai4SCIENCE has made a prominent advance, strengthening the AI researchers that will lead to compliance. Lead Strategic InterventionThe field can be seen increase in increase of ten equations in the middle of the century, convert the science.
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Source: ARXIV