Matt Grainger
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Matt Grainger
@drmattg.bsky.social
1.3K followers 2.5K following 160 posts
Interdisciplinary scientist specialising in modelling the complexities of conservation & sustainability, as well as evidence synthesis; with a sideline in pheasants. Researcher at NINA(Norwegian Institute for Nature Research), Trondheim.
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Reposted by Matt Grainger
envevidence.bsky.social
#EnvironmentalEvidence #AI #EvidenceSynthesis @biljana-macura.bsky.social
Photograph of Dr. Biljana Macura standing outdoors, wearing a white blouse, arms crossed, and smiling slightly. The photo is credited to SEI. Next to her is a quote that reads: “AI opens new possibilities for evidence synthesis, and CEE remains committed to ensuring that technology serves our goal of generating transparent, reliable and timely evidence for better environmental decisions. Using AI with human oversight remains essential.” Below the quote, it says: “Dr. Biljana Macura, Co-author of the 2025 position statement on artificial intelligence (AI) use in evidence synthesis and Co-Editor-in-Chief, Environmental Evidence.” At the bottom right is the logo for the Collaboration for Environmental Evidence.
November 11, 2025 at 12:31 PM
Reposted by Matt Grainger
katiecorker.bsky.social
We've got loads of resources here for people to get started and be convinced to try it: asapbio.org/about/why-pr...
Why Preprints? – ASAPbio
Discover how preprints accelerate scientific discovery, increase visibility of research, and enable rapid feedback while maintaining research quality standards.
asapbio.org
October 25, 2025 at 6:40 PM
Reposted by Matt Grainger
olivia.science
please think about this deeply & consult with experts who do NOT have Conflicts of Interest! See:

Guest, O., Suarez, M., Müller, B., et al. (2025). Against the Uncritical Adoption of 'AI' Technologies in Academia. Zenodo. doi.org/10.5281/zeno...

bsky.app/profile/oliv...
olivia.science Olivia Guest · Ολίβια Γκεστ @olivia.science · Sep 6
Finally! 🤩 Our position piece: Against the Uncritical Adoption of 'AI' Technologies in Academia:
doi.org/10.5281/zeno...

We unpick the tech industry’s marketing, hype, & harm; and we argue for safeguarding higher education, critical
thinking, expertise, academic freedom, & scientific integrity.
1/n
Abstract: Under the banner of progress, products have been uncritically adopted or even imposed on users — in past centuries with tobacco and combustion engines, and in the 21st with social media. For these collective blunders, we now regret our involvement or apathy as scientists, and society struggles to put the genie back in the bottle. Currently, we are similarly entangled with artificial intelligence (AI) technology. For example, software updates are rolled out seamlessly and non-consensually, Microsoft Office is bundled with chatbots, and we, our students, and our employers have had no say, as it is not considered a valid position to reject AI technologies in our teaching and research. This is why in June 2025, we co-authored an Open Letter calling on our employers to reverse and rethink their stance on uncritically adopting AI technologies. In this position piece, we expound on why universities must take their role seriously toa) counter the technology industry’s marketing, hype, and harm; and to b) safeguard higher education, critical thinking, expertise, academic freedom, and scientific integrity. We include pointers to relevant work to further inform our colleagues. Figure 1. A cartoon set theoretic view on various terms (see Table 1) used when discussing the superset AI (black outline, hatched background): LLMs are in orange; ANNs are in magenta; generative models are in blue; and finally, chatbots are in green. Where these intersect, the colours reflect that, e.g. generative adversarial network (GAN) and Boltzmann machine (BM) models are in the purple subset because they are both generative and ANNs. In the case of proprietary closed source models, e.g. OpenAI’s ChatGPT and Apple’s Siri, we cannot verify their implementation and so academics can only make educated guesses (cf. Dingemanse 2025). Undefined terms used above: BERT (Devlin et al. 2019); AlexNet (Krizhevsky et al. 2017); A.L.I.C.E. (Wallace 2009); ELIZA (Weizenbaum 1966); Jabberwacky (Twist 2003); linear discriminant analysis (LDA); quadratic discriminant analysis (QDA). Table 1. Below some of the typical terminological disarray is untangled. Importantly, none of these terms are orthogonal nor do they exclusively pick out the types of products we may wish to critique or proscribe. Protecting the Ecosystem of Human Knowledge: Five Principles
October 9, 2025 at 8:53 AM