Researcher Perspectives

What researchers think about the use of AI in research

OUP Press

Are academic researchers embracing or resisting generative AI? And how should publishers respond?

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Wiley

ExplanAItions: an Artificial Intelligence Study | April 2024

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Nature

AI and science: what 1,600 researchers think, September 2023

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Sage

New Technology from Sage Report Explores Librarian Leadership in the Age of AI, May 2025

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Nature

Is it OK for AI to write science papers? Nature survey shows researchers are split, May 2025

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STM

Generative AI in Scholarly Publishing: Ethical Guidelines for the Use of Generative AI in the Publication Process | December, 2023

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The latest AI news from STM

Inside STM’s November visit to Japan: key themes, takeaways & what’s next

In early November, STM CEO Caroline Sutton spent several days in Tokyo meeting with funders, government leaders, research agencies, and publishing groups — alongside delegates from STM’s Japan Chapter. As in last year’s visit, the conversations were productive, wide-ranging, and grounded in strong local partnerships. And while open science dominated the agenda in 2024, this…

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Announcing the selected presenters for the upcoming STM Innovator Fair

Meet the 14 startups and companies selected to present at this year’s STM Innovator Fair – a cornerstone of the upcoming STM Innovation & Integrity Days in London, 9-10 December. Selected from a record-breaking number of submissions this year, these innovators showcase some of the most promising technologies and ideas shaping the future of trusted…

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STM responds to AI labelling consultation

Article 50 of the AI Act establishes obligations for transparent labelling of AI-operated systems and AI-generated content. Publishers’ use of AI in the publishing process is very likely to fall under exemptions from such obligations, but translations remain a grey area and good practices are encouraged.

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EU adopts strategy for AI in science

The EU will establish a Resource for AI in Europe (RAISE), a virtual institute/network that coordinates key elements of the strategy: talent, compute/infrastructure, data, and funding. This will be complemented by the Data Union Strategy, expected by October/November, which aims to “ensure the availability of high-quality, large-scale datasets essential for training AI models.” | Access the…

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