How mega-science and AI are challenging traditional science journalism
By
Chris Mooney
Summary
The article discusses the challenges of science communication in an era of "mega-science" — where approximately 3.5 million scientific studies are published annually. It explores how traditional "study story" models of science journalism are becoming inadequate, especially with AI's ability to rapidly produce such stories. The author reflects on the overwhelming volume of scientific output and the difficulties journalists and communicators face in covering it meaningfully, while also addressing the systemic issues in how science is produced, funded, and communicated to the public.
Source
bskyHow mega-science and AI are challenging traditional science journalismreportearth.substack.comKey quotes
· 3 pulledIn my last post here, I wrote about problems with the 'study story' model of science journalism, especially given the arrival of AI, which can potentially churn out these stories far more rapidly than human writers can.
The post was one of my most popular so far here on Substack, and drew some notable responses.
How do we communicate about -- or as journalists, cover -- 3.5 million scientific studies per year?
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