Curious about the competing interests statesments for @i4replication.bsky.social’s @pnas.org paper. 1) funding for i4r comes heavily from an AI/tech tied group and 2) that many authors and none has a conflict of interest with LLMs and science? pnas.org/doi/10.1073/pnas.2524747123
PNAS
www.pnas.orgJul 12, 2026 at 9:49 AM
Shahan Ali Memon (@shahanmemon.bsky.social)
Researching {science of AI-mediated science, metascience #SciSci, #AI4Science, #GenAI, LLMs, agents, alignment, AI governance, misinformation in science} PhD @ UW. Visiting @ NYU & MSR Alum @ Carnegie Mellon Academic webpage: https://samemon.github.io
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An editorial was published in Nature recently claiming that glam journal publication of LLMs (like DeepSeek-R1 this case) marks a step towards greater transparency, accountability & credibility nature.com/articles/d41586-025-02979-9. I have thoughts ... 1/
https://www.nature.com/articles/d41586-025-02979-9
t.co1/7 Proud to share our paper, accepted as an oral at ICML '26! We highlight how Big Tech’s influence on AI R&D drives damaging outcomes, and what we as researchers can do about it. We also discuss underlying economic causes. See link for paper, and below for a brief summary arxiv.org/abs/2512.03077
My boiling hot take on this is that, if tech companies are going to fund this kind of research (looking at Schmidt too), then the money needs to be given *no strings* to an independent arm's length research body, pooled with other funding, and treated as a donation not as direct funding.
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Remarkable how over a decade ago @michaelnielsen.bsky.social pointed the way towards solving long standing issues plaguing science to this day (issues that are all the more relevant in the age of AI mediated science)
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This is why @atproto.science is so relevant rn This compilation of essays indicates that scientists are most frustrated by insufficient “community tools and resources... Essential infrastructure for sharing, maintaining and building on existing work and data is also badly underdeveloped." >
1/7 Proud to share our paper, accepted as an oral at ICML '26! We highlight how Big Tech’s influence on AI R&D drives damaging outcomes, and what we as researchers can do about it. We also discuss underlying economic causes. See link for paper, and below for a brief summary arxiv.org/abs/2512.03077
