A Beginner's Guide to AI · Aug 12, 2026 · 49:34
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AI in scientific publishing is changing what researchers trust, what journals reward, and what the public thinks counts as evidence. In this episode, Joy Moore and Kent Anderson unpack how the internet pushed science publishing toward scale, how open access changed incentives, and how paper mills, predatory publishers, and AI slop made the scientific record harder to defend.
They also explain why LLMs create a new problem on top of an old one. Once scientific papers are copied, summarized, remixed, and scattered across preprints, accepted manuscripts, and published versions, it becomes much harder to correct errors or retract bad information. For science, that is not a small technical issue. It is a trust issue.
For business leaders, researchers, and anyone using AI tools to make decisions, this episode is a reminder that source quality still matters. Not every paper is useful. Not every signal is reliable. And not every “science” product deserves your trust.
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Dietmar Fischer is a podcaster and AI marketer from Berlin.
If you want help with AI strategy or digital marketing, visit:
00:00 Opening and episode framing
01:57 How internet incentives changed scientific publishing
06:38 Fake diseases, preprints, and downstream AI ingestion
10:47 AI slop, fake citations, and abused data sets
16:48 Why public-facing science deserves suspicion
24:08 Centralized AI versus decentralized science
34:29 What can still be fixed in publishing
42:29 Where to find the guests and the book
Official site: disruptedscience.com
Podcast: disruptedscience.podbean.com
Book: How the Internet Disrupted Science by Kent Anderson and Joy Moore, published by Globe Pequot / listed by Simon & Schuster, just out now 🚀 Get it wherever you get your books!
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Episodes: A Beginner's Guide to AI