Generative AI and science communication in the physical sciences

被引：5

作者：

Biyela, Sibusiso ^{[1
]}

Dihal, Kanta ^{[1
]}

Gero, Katy Ilonka ^{[2
]}

Ippolito, Daphne ^{[3
]}

Menczer, Filippo ^{[4
]}

Schafer, Mike S. ^{[5
]}

Yokoyama, Hiromi M. ^{[6
]}

机构：

[1] Imperial Coll London, London, England

[2] Harvard Univ, Cambridge, MA 02138 USA

[3] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA

[4] Indiana Univ, Observ Social Media, Bloomington, IN 47405 USA

[5] Univ Zurich, Zurich, Switzerland

[6] Univ Tokyo, Kavli Inst Phys & Math Universe Kavli IPMU, Ctr Data Driven Discovery CD3, Tokyo, Japan

来源：

NATURE REVIEWS PHYSICS | 2024年 / 6卷 / 03期

关键词：

Physical science - Potential benefits - Science communications - Science communicators;

D O I：

10.1038/s42254-024-00691-7

中图分类号：

O59 [应用物理学];

学科分类号：

摘要：

Advances in generative AI could democratize science communication, by providing scientists with easy-to-use tools to help them communicate their work to different audiences. However, these tools are imperfect, and their output must be checked by experts. They can also be used maliciously to produce misinformation and disinformation. Seven researchers and science communicators weigh up the potential benefits of generative AI for science communication against its risks. Seven researchers and science communicators weigh up the potential benefits of generative AI for science communication against its risks.

引用

页码：162 / 165

页数：4

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