{"id":108199,"date":"2025-10-13T01:01:00","date_gmt":"2025-10-13T01:01:00","guid":{"rendered":"https:\/\/council.science\/?p=108199"},"modified":"2025-10-16T13:44:42","modified_gmt":"2025-10-16T13:44:42","slug":"ai-primers","status":"publish","type":"post","link":"https:\/\/council.science\/news\/ai-primers\/","title":{"rendered":"New primers examine AI use, environmental impacts and data in science","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"\n

Foreword<\/h2>\n\n\n\n

“Artificial intelligence (AI) is transforming science systems, offering new tools to tackle complex global challenges, and prompting an acceleration of the research process itself. At the same time, this transformative power introduces challenges that the global science community must address responsibly.\u00a0\u00a0<\/p>\n\n\n\n

The Members of the International Science Council, and its partners, have been examining the impacts of emerging technologies on science systems and society, through, for example, Navigating New Horizons<\/em><\/a> (2024) \u2013 a joint UNEP-ISC foresight report on planetary health and human wellbeing, the Royal Society\u2019s Science in the age of AI<\/em><\/a> (2024), and the ISC\u2019s framework for Evaluating rapidly developing technologies including AI, large language models and beyond<\/em><\/a> (2024). <\/p>\n\n\n\n

Since 2024, the ISC\u2019s Centre for Science Futures has taken a broader view of the impact of emerging technologies on science systems in the Global South through the Science Systems Futures<\/a> programme, where a key angle has been looking at the AI-readiness of the science systems in various countries:  Preparing National Research Ecosystems for AI<\/em><\/a> (2025).  <\/p>\n\n\n\n

The themes of the three technical primers presented here arose from points of ambiguity in many of the country case studies features in the above 2025 report. These primers aim to move beyond buzzwords and hype, providing technical and contextual grounding. They offer an objective, high-level analysis of AI’s role in the scientific process through three lenses: <\/p>\n\n\n\n

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Types of AI in science<\/a><\/p>\n<\/div>\n\n\n\n

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Considerations on the environmental impact of AI in science<\/a><\/p>\n<\/div>\n\n\n\n

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Data for AI in science<\/a><\/p>\n<\/div>\n<\/div>\n\n\n\n

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By outlining the core issues in these domains, we hope that these primers will help the scientific and science policy communities of the ISC to engage with the subject from a place of knowledge, not assumption. This is crucial for developing policies and practices that maximize AI’s benefits while mitigating its risks in science.”<\/p>\n\n\n\n

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\n \n \"\" Sir Peter Gluckman<\/span>\n <\/a>\n
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Sir Peter Gluckman<\/h2>\n
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ISC President, Distinguished Professor Emeritus ONZ KNZM FRSNZ FRS<\/p>\n <\/div>\n <\/div>\n Sir Peter Gluckman<\/a>\n <\/div>\n \n

\n \n \"David-Castle, David Castle<\/span>\n <\/a>\n
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David Castle<\/h2>\n
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Chair of the ISC Science Systems Futures project<\/p>\n <\/div>\n <\/div>\n David Castle<\/a>\n <\/div>\n <\/div>\n <\/section>\n\n\n\n\n

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This work was carried out with the aid of a grant from the International Development Research Centre (IDRC), Ottawa, Canada. The views expressed herein do not necessarily represent those of IDRC or its Board of Governors.<\/em><\/p>\n\n\n\n

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