현재 교육 분야 AI를 적용하려고 합니다.

Dear Muhammad Ehsan ,

GenAI for Research InfrastructureCode generation tools such as Copilot have become powerful and successful, leading to significant improvements in users' ability to create software to collate and analyze data. Other ways might involve using GenAI to help construct or critique survey questions or interview templates.

https://research-and-innovation.cornell.edu/generative-ai-in-academic-research/#:~:text=GenAI%20for%20Research%20Infrastructure,-One%20of%20the&text=Code%20generation%20tools%20such%20as,survey%20questions%20or%20interview%20templates.

Despite strong interest in using artificial intelligence to make research faster, easier and more accessible, researchers say they need more support to navigate its possibilities.

https://www.nature.com/articles/d41586-025-00343-5

Regards,

Shafagat

Shafagat Mahmudova Thank you so much for your insights!

GenAI is really improving research by making data handling and coding easier. It’s great to see how it can help, but careful verification is always important.

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"A new and seemingly more impressive artificial intelligence (AI) tool is released almost weekly, and researchers are flocking to try them out. Whether they are looking to edit manuscripts, write code or generate hypotheses, researchers have more generative AI tools to choose from than ever before.

Each large language model (LLM) is suited to different tasks. Some are available through free chatbots, whereas others use a paid-for application programming interface (API) that means they can be integrated with other software. A few can also be downloaded, allowing researchers to build their own custom models.

Although LLMs produce human-like responses, they all remain too error-prone to be used on their own, says Carrie Wright, a data scientist at the Fred Hutchinson Cancer Center, headquartered in Seattle, Washington.

So which LLM is best for what task? Here, researchers share their current favourites with Nature to help guide those in need..."

https://www.nature.com/articles/d41586-025-00437-0

Publishers need to provide guidelines on use of AI in research, says Wiley

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ExplanAItions was set up to survey researchers on how they are currently using AI and how they might be interested in using it in the future. In addition, Wiley wanted to uncover what researchers want from publishers in terms of guidelines, training and policies. The researchers represented a wide range of disciplines, geographies, career phases and sectors, and nearly all had previously submitted an article for publication or were planning to do so in the near future.

The survey revealed that current use of AI among researchers is fairly limited, both in terms of tools used and tasks done. However, despite this, researchers said that developing AI skills would be highly important to them personally in the near future.

Uncertainty was found to be a major barrier to making the most of AI’s potential, and nearly two-thirds of researchers cited a lack of guidance and training preventing them from using AI to the extent that they would like..."

https://www.wiley.com/content/dam/wiley-dotcom/en/b2c/content-fragments/explanaitions-ai-report/pdfs/Wiley_ExplanAItions_AI_Study_February_2025.pdf

https://www.chemistryworld.com/news/publishers-need-to-provide-guidelines-on-use-of-ai-in-research-says-wiley/4020961.article

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"Generative artificial intelligence (GnAI) has garnered significant attention worldwide across diverse industries, including in book publishing. To date, more attention has been paid to its potential in creative collaboration and less to the editorial possibilities of its application. Interest has accelerated since the breakthrough of a new Large Language Model in late 2022. This paper engages with the ethical and industrial implications of using GnAI in a creative context, namely literary publishing. It raises crucial questions about intellectual property, trust, the author–editor relationship and publishing professionals’ evolving roles in shaping quality literature. Using a published story as a test case, we compare edits using GnAI with those by professional editors over multiple drafts and at different stages of editorial development. We consider the potential ethical implications of the use of GnAI in literary fiction editing, highlighting the principles and practices that underpin professional editing to consider how these may or may not translate in the use of GnAI. This is followed by a discussion of the risks and opportunities in using GnAI in editing literary texts in the trade publishing context."

Article Ethics and the use of generative AI in professional editing