Falsifying data in a statistical analysis is a fireable offence, but erasing women from the scientific record is business as usual
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Iris van Rooij 💭
@Iris@scholar.social
mastodon 4.7.3Professor of Computational Cognitive Science | Dept. of Cognitive Science & Artificial Intelligence | http://irisvanrooijcogsci.com | Critical AI Literacy | Guest Prof at Aarhus University | she/they 🏳️🌈
3990 Followers
495 Following
50 Posts
Joined August 22, 2018
If you are doing academic work in AI, but cannot see the technofascist project called "AI" for what it is, how are we to trust your work does not support that project?
"Feel free to adapt and reuse. No attribution needed (...) If you make an adaptation that you also want to share, I’d love to know about it, too."
https://irisvanrooijcogsci.com/2026/04/08/refusal-to-review/
"In this position piece, we tease apart and explain why phrases like ‘generative AI’ impede scholarly discussion because by design these expressions are used to dazzle and sidestep scrutiny. (...) [U]niversities must take their role seriously to a) counter the AI industry’s marketing, hype, and harm; and to b) safeguard higher education, critical thinking, expertise, academic freedom, and scientific integrity." -- @olivia@scholar.social Guest et al. (2026)
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"Cease normalising the AI hype and the lies which are prevalent in the technology industry's framing of these technologies. The technologies do not have the advertised capacities and their adoption puts students and academics at risk of violating ethical, legal, scholarly, and scientific standards of reliability, sustainability, and safety."
https://openletter.earth/open-letter-stop-the-uncritical-adoption-of-ai-technologies-in-academia-b65bba1e?limit=0
Your “pro-AI in academia”-argument, accompanied by an AI slop image that has synthetic text that does not even spell real words, is not as convincing as you may think it is.
https://olivia.science/cheating/
"using AI is not victimless (...) Often you not only are the product — yes, they will steal and sell your data — but you are also robbed of learning.
When the hype inevitably dies down, as it has done many times before, through AI summers and winters (see my talk here if you were not aware of these cycles: https://www.youtube.com/watch?v=4DHgVkIWhig), you want to have skills. You want to have a degree that matters." -- @olivia@scholar.social
Don’t ask me why, but I came up with an ‘adversarial graph coloring game’, where players each color a vertex per turn, and the first player who is forced to color a vertex connected to a vertex they already coloured loses.
Is this game and its complexity known?
"While the AI industry claims its models can “think,” “reason,” and “learn,” their supposed achievements rest on marketing hype and stolen intellectual labor. In reality, AI erodes academic freedom, weakens critical reading, and subordinates the pursuit of knowledge to corporate interests." -- Olivia Guest & Iris van Rooij (2025)
https://www.project-syndicate.org/commentary/ai-will-not-save-higher-education-but-may-destroy-it-by-olivia-guest-and-iris-van-rooij-2025-10 @olivia@scholar.social
📚 ☀️
Summer School: Critical AI Literacies for Resisting and Reclaiming
https://irisvanrooijcogsci.com/2026/02/18/summer-school-critical-ai-literacies-for-resisting-and-reclaiming/ cc @olivia@scholar.social
Will AI soon surpass the human brain? If you ask employees at OpenAI, Google DeepMind and other large tech companies, it is inevitable. However, researchers @Iris@scholar.social and @olivia@scholar.social at Radboud University and others show new proof that those claims are overblown and unlikely to ever come to fruition. Their findings are published in Computational Brain & Behavior today.
https://www.ru.nl/en/research/research-news/dont-believe-the-hype-agi-is-far-from-inevitable
Advice for @ERC_Research@respublicae.eu :
Prohibit the use of LLMs for grant writing. Let applicants sign a declaration that they have not used such systems and that the text is written by them and them alone.
This is not how one avoids plagiarism.
This is how one HIDES plagiarism.
1/n
This was such a wonderful conversation! 💛
Thank you so much @mel_hogan@mstdn.ca for inviting us on The Data Fix podcast.
And thank you @olivia@scholar.social Guest and Andrea Reyes Elizondo for sharing your amazing insights and important angles.
🎶 You can all listen here:
https://shows.acast.com/the-data-fix/episodes/hollowed-with-olivia-guest-iris-van-rooij-and-andrea-reyes-e 🎶
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"our goals below are twofold:
a) to clarify what our approach to theory and models is and proposes, especially for junior scholars entering the field, and with respect to what role prediction plays
in our modelling; and
b) to further the scholarly exchange of ideas on contemporary theorising (...) which is under attack in the context of artificial intelligence (AI) and promote discussion of related ontological issues"
--- Guest, Martin, & van Rooij (2026)
https://scholar.social/@olivia/116510479584933460
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RE: https://dmv.community/@jcrabapple/116846329747286727
What could possibly go wrong? 👀
Quoting
Scientists built a cell from scratch for the first time. It feeds, grows, replicates its DNA, and divides. Called SpudCell.
36 genes, 90K base pairs, 150-200 molecules. Not alive (can't make ribosomes, can't evolve, needs constant feeding) but it's the first complete cell cycle from entirely non-living components.
https://www.quantamagazine.org/for-the-first-time-a-cell-built-from-scratch-grows-and-divides-20260701/
#syntheticbiology #science #biology
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@jdp23@neuromatch.social @olivia@scholar.social Here a link with info, in case useful, thank you 
https://irisvanrooijcogsci.com/2026/02/18/summer-school-critical-ai-literacies-for-resisting-and-reclaiming/
https://irisvanrooijcogsci.com/2026/02/18/summer-school-critical-ai-literacies-for-resisting-and-reclaiming/Important thread 🧵
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"The term ‘Artificial Intelligence’ (AI) means many things to many people (see Table 1) (...). One meaning of ‘AI’ that seems often forgotten these days is one that played a crucial role in the birth of cognitive science as an interdiscipline in the 1970s and ’80s." 2/n
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"present-day AI hype [leaves] little room for AI as a theoretical tool for cognitive science. Worse even, the products of ... AI-as-engineering are sometimes believed to instantiate (parts of) minds. (...) [This] view deteriorates our theoretical understanding of cognition" 4/n
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"This view of ‘AI’ as a research field overlapping with psychology sees computational systems as theoretical tools (...) Accordingly, AI is one of the cognitive sciences (Figure 1), and for decades there was a close dialogue between the fields of AI and cognitive psychology." 3/n
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@dramypsyd@ohai.social I think it matters little, and may even help students focus on content of slides more
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(Contrast to Simon, a more sensible perspective further back in history. >100 years before cogsci was formed as an interdiscipline, Ada Lovelace warned against "the possibility of exaggerated ideas ... as to the powers of the Analytical Engine ["AI"]." (see also ACT 1) 13/n
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ACT 2: "Based on our analysis [in Act 1], we reject the view and associated project that we term ‘makeism’. See Box 2 for a definition." 10/n
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CONCLUSION:
AI-as-engineering has been trespassing into cogsci, confusing us with decoys. The time is apt to reclaim the early conception of AI-as-theoretical-psychology. This means using AI as a theoretical tool; but we want to not fall in the trap of makeism again. 17/n
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ACT 1 (cont'd) Even if AI-by-Learning may be practically solvable for simple situations (small n), any attempts to scale up to situations of real-world, human-level complexity (medium to large n) will necessarily consume an astronomical amount of resources (see Box 1). 8/n
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Given the Ingenia Theorem, how to interpret what's happening in practice?
It implies, if you test AIs rigorously for human-likeness, it quickly becomes evident they behave qualitatively differently from humans. Unsurprisingly, we see exactly this play out.
[end of ACT 1]. 9/n
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ACT 1 (cont'd): We present The Ingenia Theorem: AI-by-Learning is intractable (formally, NP-hard). The proof is by reduction from a known NP-hard problem (in this case Perfect-vs-Chance, proven intractable by Hirahara, 2022). See APPENDIX for full details. 7/n
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ACT 1: We introduce a hypothetical engineer, Dr. Ingenia, who wants to make human (-like or level) AI using ML. We grant highly simplified and idealised conditions (perfect data, access to all ML methods present & future, low bar) and formalise the AI-by-Learning problem. 6/n
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@DrSuzanne@ohai.social @OpenTech_AUC@social.edu.nl @olivia@scholar.social You can sign our letter too! We welcome signatures from anyone in (or who feels connected to) academia
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ACT 2 (cont'd): We explain how computationalism can aid cogsci without makeism, referring to examples from existing work:
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Levels of explanation;
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Capacities as problems;
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Algorithms and simulations;
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Underdetermination;
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Computational realisability.
15/n
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ACT 2 (cont'd): In reclaiming AI for cogsci, we need to make sure not to repeat conceptual mistakes of the past, and prevent the rerun of history.
Makeism & overstatements of AI possibilities is of all times. Note the date on H. Simon's quote.
This we shouldn't reclaim. 12/n
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We aim to remedy the situation in 2 "acts": In Act 1 we set out to release the grip of the currently dominant view of AI-as-engineering and reveal a fatal conceptual error. In Act 2 we reclaim AI for theoretical psychology without falling into historical & present-day traps. 5/n
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ACT 2 (cont'd): "the reader may wonder: if we indeed cannot (re)make cognition—or coherent parts of cognition—computationally, then is AI theoretically useless for cognitive science? No: computationalism can be theoretically productive even if makeing is futile." 11/n
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ACT 2 (cont'd): To genuinely make progress we need to go slowly. Only then can AI be a useful theoretical tool for cogsci & regain its rightful place in the interdisciplinary hexagon. 16/n
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In this position you will be embedded in the Computational Cognitive Science group at the Donders Institute. In this group we aim, among other things, at advancing the theoretical foundations of computational explanations in cognitive science (i.e., the multidisciplinary study of cognition). https://www.ru.nl/donders/research/theme-2-perception-action-decision-making/research-groups-theme-2/computational-cognitive-science/ ⬇️
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Application form will be online a.s.a.p. This pre-announcement is to give early notice. More info below in this thread.
Interested? ➡️ Bookmark this thread.
We especially welcome applications from women & non-binary people and/or otherwise minoritized applicants. Come join us!🌈