iiinova — where your digital self keeps evolving

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Olivia Guest · Ολίβια Γκεστ @olivia.science · 11/06/2026

💥 @lucyavraamidou.bsky.social saying it like it is about AI in her keynote: Learning to live with the world: The role of STEM education www.conftool.org/smec2026/ses...

A slide on a big screen that says:
The AI inevitability narrative and then next to it a photo of a mural that says Fuck this imperialist bullshit with Lea Morgana

On the right is Lucy presenting what I can only imagine is the coolest keynote ever

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Marcela Suarez @marentierra.bsky.social · 14/05/2026

Our position paper is out! Read it now in the following link:

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Olivia Guest · Ολίβια Γκεστ @olivia.science · 14/05/2026

Published with some minor changes! Please share widely. 😊 Guest, O., Suarez, M., ... & van Rooij, I. (2026). Against the Uncritical Adoption of 'AI' Technologies in Academia. Digital Culture & Education, 16(2), 85–118. doi.org/10.5281/zeno... Journal: www.digitalcultureandeducation.com/volume-162

digitalcultureandeducation.com

Volume 16.2 — Digital Culture & Education (ISSN: 1836-8301)

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Olivia Guest · Ολίβια Γκεστ @olivia.science · 08/04/2026

Demystifying AI: The urgency of a critical stance on the use of AI systems in education Dagmar H & @lucyavraamidou.bsky.social > The education field has [embraced AI for the] (undocumented) potential to reduce teacher workload, address inequalities, and enhance learning doi.org/10.1007/s111...

Demystifying AI: The urgency of a critical stance
on the use of AI systems in education
Dagmar Mercedes Heeg1
· Lucy Avraamidou2
Received: 25 November 2025 / Accepted: 8 February 2026
© The Author(s) 2026
Abstract The education field has generally embraced artificial intelligence (AI) systems
for their (undocumented) potential to reduce teacher workload, address inequalities, and
enhance learning through personalization. However, issues such as algorithmic bias, mono-
culturalism, discrimination, use of private data, and access to AI systems raise concerns
about exacerbating learning inequalities, especially for minority students. We argue that
researchers in education have largely failed to critically address the limitations of AI sys-
tems, and that a critical stance framed within critical AI literacies is urgently needed to
ensure responsible use, if any, of AI systems in the classroom. We first examine how AI
systems have been conceptualized for educational purposes. Through engagement with
related literature, we discuss what has been overlooked by the mystifying of AI and the
failure to engage more thoroughly and critically with existing literature on the social nature
of learning. Following that, we provide an overview of contemporary AI literacy frame-
works through a comparative approach and discuss their potential and limitations. We con-
clude with a set of recommendations for future research, teacher education, and curriculum
design, framed within a critical stance to foster fair, ethical, and responsible use, where
appropriate, of AI systems in education.
Keywords AI · Education · Critical AI literacies

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Olivia Guest · Ολίβια Γκεστ @olivia.science · 17/12/2025

Coming out of 3 week migraine (status migrainosus, look it up) & seeing my work — w/ @marentierra.bsky.social @irisvanrooij.bsky.social @altibel.bsky.social @jedbrown.org @felienne.bsky.social @lucyavraamidou.bsky.social — in Rolling Stone. Guess I shouldn't be as depressed anymore based on facts 😌

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Iris van Rooij 💭 @irisvanrooij.bsky.social · 14/10/2025

Critical AI Literacy Symposium, with Dagmar Monett, @lucyavraamidou.bsky.social & Miquel Pérez Torres, Linda Mannila, and @olivia.science 🎬 Video recording: www.youtube.com/watch?v=Fxyg... 📢 Symposium website: www.ru.nl/en/about-us/... 🤔 Critical AI Literacy website: www.ru.nl/en/research/...

youtube.com

Critical AI Literacy: Empowering people to resist hype and harms in the age of AI -- Symposium 2025

YouTube video by Iris van Rooij

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Olivia Guest · Ολίβια Γκεστ @olivia.science · 21/09/2025

Getting close to 50k views and I'm wondering is it just everybody is scared to say this and pleased I did? Because if there's so many of us who agree, trust me I'd know if 1k people disagreed with me let alone 50k, why are we letting AI ruin our universities? Together we can turn back the tide.

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Olivia Guest · Ολίβια Γκεστ @olivia.science · 08/09/2025

Can you all explain yourselves what the actual f is 23k views and about half as many downloads on a preprint right now come off it 🥺

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Olivia Guest · Ολίβια Γκεστ @olivia.science · 06/09/2025

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

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