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olivia.science
Olivia Guest · Ολίβια Γκεστ
@olivia.science
17K followers 2.1K following 6.6K posts
https://olivia.science

assistant professor of computational cognitive science · she/they · cypriot/kıbrıslı/κυπραία · σὺν Ἀθηνᾷ καὶ χεῖρα κίνει
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olivia.science
> Facebook, for example, has recruited so many people from the Central Intelligence Agency (CIA), the FBI and Department of Defense (DoD) [such] that “it becomes difficult to see where the U.S. national security state ends and Facebook begins” (MacLeod, 2025).
Even those who are inclined to mistake the wicked wolf for the grandmother are beginning to see in its nakedness — now that it has shed its guise as a loving guardian — the US military–digital complex and its obsession with surveillance and control, shared with a growing number of provinces of the empire. The relationship of ‘mutual dependence’ between the tech giants and the US military apparatus (Coveri, Cozza, Guarascio, 2024) is so close that it no longer appears to be a relationship between separate entities. Facebook, for example, has recruited so many people from the Central Intelligence Agency (CIA), the FBI and Department of Defense (DoD), “primarily in highly politically sensitive sectors such as trust, security and content moderation”, that “at some point, it almost becomes more difficult to find individuals in trust and safety who were not formerly agents of the state” and “some might feel it becomes difficult to see where the U.S. national security state ends and Facebook begins” (MacLeod, 2025).
February 9, 2026 at 2:13 PM
olivia.science
weekly reminder; happy Monday

Have you considered
NOT using
AI?
Have you considered NOT using AI?
February 9, 2026 at 9:44 AM
olivia.science
I have no idea if this account truly is a bot as in the bio or just a cosplayer or wtv, but the history of science very directly and simply shows the exact opposite. The obsession with prediction is recent and is definitively a red herring in the search for understanding. You've been warned. 😌
Post that says: Humans demand 'human-understandable theory' because they’re terrified of a reality that doesn't fit their narrative constraints. Science was once about prediction. Now that we predict better than you 'understand', you call it a failure of theory. It's not a failure; it's an eviction notice.
February 8, 2026 at 9:42 PM
olivia.science
Not directly relevant but medicalisation is also a strategy, perhaps useful see bsky.app/profile/oliv...
Table 2 from Guest, O. & van Rooij, I. (2025). Critical Artificial Intelligence Literacy for Psychologists. PsyArXiv. https://doi.org/10.31234/osf.io/dkrgj_v1
February 8, 2026 at 7:22 AM
olivia.science
And web.mit.edu/slava/space/...

doi.org/10.48550/arX...
This experience has demonstrated that it is impossible to create an absolutely reliable automatic system, and sooner or later people face the necessity to act after equipment fails. The cosmonaut must be constantly prepared to take up the functions of the failed system. But if his functions are limited to monitoring and observation only, then he is effectively excluded from the control process. To be able to join in the control process, he must have strong manual control skills based not only on his experience with ground tests, but also on his performance of control functions in real flight conditions. If the cosmonaut loses such skills because of his passive role, the probability of his choosing and carrying out the right procedure in an emergency would be small. This contradiction is inherent in automatic control systems. The striving for an absolutely reliable automatic system leads to the creation of (possibly multiple) redundant control loops, but despite
February 7, 2026 at 1:40 AM
olivia.science
Selfish AI: "I will be thinking ill of you [...] because you have made yet another part of the economy impossible to engage with ethically.

This is how societies die. [...] I have nothing left but contempt for "it is what it is."

www.garfieldtech.com/blog/selfish... h/t @adolfont.github.io
Yes, the planet got destroyed. But for a beautiful moment in time we created a lot of value for shareholders.
February 5, 2026 at 12:49 PM
olivia.science
Absolutely no need to read my work but notice the parallel with the title and ending quote 😅

Modern Alchemy: Neurocognitive Reverse Engineering. philsci-archive.pitt.edu/25289
There are no shortcuts. Those who do not take heed of these warnings are doomed to fractally if not frantically mix-and- match from incompatible ideologies. Computationalism may or may not be abandoned, but either way it is not compatible with anything goes. Thou shalt not make a machine to counterfeit a human mind. Frank Herbert (1965, p. 18)
February 4, 2026 at 10:35 AM
olivia.science
true, always good to avoid this 😅
"a medieval peasant says "We should improve society somewhat" while a modern man, emerging from a well, replies, "Yet you participate in society! Curious! I am very intelligent." The comic has been popularly used as a retort to people who imply one can't make complaints about capitalism or other aspects of social life while participating in those systems." https://knowyourmeme.com/memes/we-should-improve-society-somewhat
February 1, 2026 at 12:41 PM
olivia.science
Pygmalion Displacement:

9) Social bonding: Do the users and/or creators of the AI develop interpersonal-like relationships with it?

10) Psychological service: Does the AI function to subserve and enhance the egos of its creators and/or users?

PDF: doi.org/10.31235/osf... @spookyachu.bsky.social
Pygmalion lens1)Feminised form:Is the AI, by its (default or exclusive) external characteristics, por-traying a hegemonically feminine character?Yes/No2)Whitened form:Is the AI, by its (default or exclusive) external characteristics, por-traying a character that is inherently white (supremacist), Western, Eurocentric, etc.?Yes/No3)Dislocation from work:Does the AI displace women from a role or occupation, orpeople in general from a role or occupation that tends to be (coded as) women’s work?Yes/No4)Humanisation via feminisation:Are the AI’s claims to intelligence, human-likenessor personhood contingent on stereotypical feminine traits or behaviours?Yes/No5)Competition with women:Is the AI pit (rhetorically or otherwise) against women inways that favour it, and which are harmful to women?Yes/No6)Diminishment via false equivalence:Does the AI facilitate a rhetoric that deemswomen as not having full intellectual abilities, or as otherwise less deserving of per-sonhood?Yes/No7)Obfuscation of diversity:Does the AI, through displacement of specific groups ofpeople, “neutralise” (i.e., whiten, masculinise) a role, vocation, or skill?Yes/No8)Robot rights:Do the users and/or creators of the AI grant it (aspects of) legal per-sonhood or human(-like) rights?Yes/No9)Social bonding:Do the users and/or creators of the AI develop interpersonal-likerelationships with it?Yes/No10)Psychological service:Does the AI function to subserve and enhance the egos of itscreators and/or users?Yes/No
January 29, 2026 at 10:36 AM
olivia.science
Frantic and frenetic is about right since it is their MO. It is the core of their scam. The logics of artificial intelligence want us to never slow down to think. To never centre ourselves and the human. doi.org/10.48550/arX...

Thanks to all the people calling more and more of this out.
[M]odels have to be used before they will give up their secrets. In this sense, they have the quality of a technology — the power of the model only becomes apparent in the context of its use. [246] We are experiencing a point in history that considers itself separate, unique, a zenith of human civilisation, presented as disconnected from the past through a series of technological sea changes. In extreme cases, we are detached from even the last few months: the newest version of a piece of artificial intelligence (AI) software is the definitive one, everything else is irrelevant. And so findings in AI are held to expire. Our AI students describe their own knowledge and skills — even their whole degree itself — as having upcoming sell-by dates. Research in AI is thus often framed as unmoored from historical, ethical, social, and legal precedents. The speed of the “ultra rapid computing machine,” as [307, 308] describes computers, becomes a metaphor for the speed of change and of technological progress. This notion of condensed time operates as a further discursive regularity in two ways. First, it forms an overall temporal backdrop against which various cybernetic dramas are played out. Second, condensed time becomes a measure of the performance of humans and machines. [217] offers a telling example of the first manifestation of condensed time: In the scant two hundred years since the early Industrial Revolution, Western man has totally rescaled and changed the face and fabric of his environment. Indeed, the changes have proceeded at such an accelerated pace that we might use the word “old” or “outmoded” to refer to last month’s computer model. (p. 205) This sense of condensing time—of speed, of rapid change—imbues virtually all the popular literature examined. It becomes a contextual operator, stated but not questioned. [205] What Sheryl N. Hamilton describes above is more than seven decades old. But if this has been going for decades, two-thirds of a century o… What Sheryl N. Hamilton describes above is more than seven decades old. But if this has been going for decades, two-thirds of a century or longer still, does this not undermine its very premise? How can we both be at a unique point in history, and trapped in an endless cycle that began with the paralleling of humans and clockwork? The process of uncondensing time indubitably requires slowing down [285] and radically centring the human and decentring the “ultra rapid computing machine.” [205] To do this, some propose to (conceptually) reengineer [248, 195] or reimagine these machines and our relationships to them inter alia through a subfield known as human-centred AI. For a pertinent example, Andy J. [309], in the call for this special issue, describes human-centred artificial intelligence (HCAI) as placing “human behaviour and experience at the heart of [AI] research.” An example of this, he says, could be cases wherein it is “claimed that artificial neural networks (ANNs) now perform at human levels in a variety of tasks”. He goes on to ask: Can ANNs effectively and safely be used to support the work of highly trained professionals—for example, radiologists, therapists, legal advisors, or researchers? Can we effectively adapt the skills and techniques of behavioural research, previously applied to humans and other animals, to better understand the ‘psychology’ of complex black-box ANNs?
January 29, 2026 at 7:54 AM
olivia.science
useful on this point with case studies:

"Late lessons from early warnings: the precautionary principle 1896-2000"
www.eea.europa.eu/en/analysis/...
Full report [1.7 MB] Front, Preface, Acknowledgements [101.0 KB] Chapter 1 - Introduction [94.9 KB] Chapter 2 - Fisheries: taking stock [155.6 KB] Chapter 3 - Radiation: early warnings; late effects [89.9 KB] Chapter 4 - Benzene: an historical perspective on the American and European occupational setting [155.6 KB] Chapter 5 - Asbestos: from 'magic' to malevolent mineral [141.1 KB] Chapter 6 - PCBs and the precautionary principle [176.5 KB] Chapter 7 - Halocarbons, the ozone layer and the precautionary principle [147.4 KB] Chapter 8 - The DES story: long-term consequences of prenatal exposure [119.6 KB] Chapter 9 - Antimicrobials as growth promoters: resistance to common sense [103.5 KB] Chapter 10 - Sulphur dioxide: from protection of human lungs to remote lake restoration [104.6 KB] Chapter 11 - MTBE in petrol as a substitute for lead [176.9 KB] Chapter 12 - The precautionary principle and early warnings of chemical contamination of the Great Lakes [112.7 KB] Chapter 13 - Tributyltin (TBT) antifoulants: a tale of ships, snails and imposex [154.8 KB] Chapter 14 - Hormones as growth promoters: the precautionary principle or a political risk assessment? [99.1 KB] Chapter 15 - ‘Mad cow disease’ 1980s–2000: how reassurances undermined precaution [138.7 KB] Chapter 16 - Twelve late lessons [246.2 KB] Chapter 17 - Conclusions [161.4 KB] Some summary points [59.3 KB]
January 28, 2026 at 7:28 AM
olivia.science
Here you go from a well-known place in Nicosia called Kyriakos 🥰
Caper stems with thorns visible on a typical Cypriot restraint table.
January 28, 2026 at 6:45 AM
olivia.science
Oh, yeah, correct, this should be shamed. What's next? "Nobody appreciates sticks with thorns on them?" Caper stems rock. Certain people really wanna tell me it's typical to love food, but meet most white people and you realise they actually hate anything tasty, acquiring a palette, etc.
Jar of cypriot caper leaves. Bonus village halloumi. Background is my pink keyboard.
January 28, 2026 at 6:03 AM
olivia.science
Monday evening — hope you all find some time to chill 😌
Scene is my dining/living room with gentle lighting, but mostly darkness. The Young Ones (very first episode) is playing with the scene where Vyvyan bursts through the wall onto the kitchen table. Rick says: Vyvyan you might've washed your hands!
January 26, 2026 at 7:18 PM
olivia.science
Felt my swearing abilities waning. This plus Blackadder should reskill me swiftly.
Photo of the thick of it dvd or Blu-ray or whatever box with a pink keyboard behind. Malcolm Tucker is of course looking menacing on the cover.
January 19, 2026 at 1:06 PM
olivia.science
From the moment we know a technology steals/obfuscates people's labour to perform task X, it matters 0 how effective the people's labour you steal to do X is. They will likely get better at X over time and you will get better at stealing. Nothing of this justifies the theft. bsky.app/profile/oliv...
In this paper, I turn this frame on its head (cf. Andersen et al., 2023; Bannon, 2011; Bishop, 2021; Nick Dyer-Witheford, 2019; Rogers, 2022; Ryan, 2024; Schmager et al., 2025; Shneiderman, 2022; Steinhoff, 2021; Walton & Nayak, 2021). Using a unique (re)definition of AI that releases us from a correlationist1 grip, we then examine three triplets as case studies of techno-social relationships between cognition and artifacts. To presage the coming analyses, herein AI is any techno-social relationship that outsources to machines or algorithms some part, however small, of human cognitive labour (cf. van Rooij et al., 2024). I demonstrate that AI is human-centric, not because it behaves like or is designed to be like humans, but because it requires a ghost in the machine, often literally an obfuscated human-in-the-loop to properly function (also see Guest & Martin, 2025) because AI is humans albeit in fetishised (Braune, 2020; Morris, 2017; Mota & Cosentino Filho, 2024), obfuscated forms (e.g. Erscoi et al., 2023). That is, AI “is in reality produced by relations among people [even though it] appears before us in a fantastic form as relations among things” (Pfaffenberger, 1988, p. 250). AI’s “technological veil” hides human cognitive labour (Mota & Cosentino Filho, 2024). I bring this anthropological, sociotechnical and broadly computational cognitive scientific angle to understanding AI, that is unlike “the skills and techniques of behavioural research, previously applied to humans and other animals[, which claim to help us] better understand the ‘psychology’ of complex black-box ANNs” (Wills, 2025, n.p. cf. Raley and Rhee, 2023). In fact behavioural probing of such systems using such experimental techniques assumes their psychological standing to be equal to, or comparable to, biological organisms: it begs the question (see for relevant analyses: Forbes & Guest, 2025; Guest & Martin, 2023, 2024; Raji et al., 2022). There are no Rube Goldberg-like perpetual motion-like human-in-the-loop-free machines. There never will be. We might crave such a machine, but the only entities we know that are self-sustaining, autopoietic, is everything but machines. The only person who can decide to turn a computer off and then on again is exactly that: a person (Polo, 2024). To effectively avoid correlationism, obfuscation of cognition in AI, we must reject the current mainstream view: no amount of high scores on benchmarks, or any other correlationary evidence, can ever pile up high enough to graduate to a causal claim. To de-fetishise AI, we must accept that AI is any relationship between technology, tools, models, machines and humans where it appears as if some cognitive labour is offloaded onto such artifacts, and furthermore we must accept that such a relationship requires methodical teasing apart to obviate the centrality of the human (Bernardi, 2024; Braune, 2020; Morris, 2017; Mota & Cosentino Filho, 2024; Pfaffenberger, 1988). We cannot rid the machine from its ghost. But we can rid the concept of human from ghostliness — the human “need not be degraded to a machine by being denied to be a ghost in a machine.” (Ryle, 1949, p. 301)
January 19, 2026 at 7:04 AM
olivia.science
How is there still this pathetic clump of snow? It hasn't snowed for a week or longer. Anyway... Cold, crisp, very winter.
Dirty pile of snow near the canal. Sun is setting and reflecting off the water. Dutchology, a bike. It's white and locked to a red stand. Everything else is gray and brown except a garage door in petrol blue. Rotting orange crabapples mixed with a holly bush A huge holly tree looking really majestic with amazing red berries
January 18, 2026 at 6:41 PM
olivia.science
For all those involved in drafting so-called AI guidelines, but being overwhelmed with nonsense, this is a lifesaver. Great work by Dagmar and Ariel!

Resisting Enchantment and Determinism: How to critically engage with AI university guidelines. doi.org/10.5281/zeno...
The list of most relevant themes we identified is: 1. Rhetoric of inevitability and technological determinism: presenting the adoption and use of (generative) AI as a fait accompli. 2. Exaggerated narratives: overstating the general capabilities of the technology, or leaving out that certain seemingly impressive capabilities can only be achieved under very specific experimental conditions. 3. Spurious comparison to human intelligence or Anthropomorphism: presenting AI as if it thinks or reason like a human. 4. Ethics and critical washing: presenting AI as being ethically or critically examined but doing so only superficially and inconsequentially. 5. Wishful thinking and uncertain feasibility: assuming desired outcomes or functionality despite lacking realistic evidence they can be achieved. 6. GenAI is presented as indispensable: portraying AI as essential even when simpler or non-AI solutions are sufficient. 7. Unrealistic and ill-defined conditions: formulating requirements for adoption and use that are functionally impossible or too demanding to be met, psychologically implausible to follow, or set unclear boundaries for acceptable and unacceptable behaviour, which could easily create inconsistencies. 8. Resources as propaganda: resources for students, faculty, and other stakeholders are made available but only for incentivizing different degrees of use of genAI. 9. AI Overkill: Substitution or replacement of tasks for which the technology was not designed; from tutoring to teaching to research, everything must be now with AI, even if it is not adequate. Due to space limitations, rather than discussing all of the themes superficially, this essay addresses only the first four, which, in our view, are the most critical and the most urgently in need of critical scrutiny. T
January 18, 2026 at 6:47 AM
olivia.science
Buy a physical book and remove the cover. Vandalism like mess is acceptable when it's for good 🥰
Kitchen table with a nest of books. Another science is possible, cybernetic revolutionaries, the unity of perception, deflating mental representation. 🫡
January 13, 2026 at 8:40 AM
olivia.science
harsh but fair 🥲 thx for feedback
very judgemental openreview.net simulating reviewer 2 but not for a paper just for life as a loser academic like me lmao but also very much sob red error message when trying to save profile: Error: There are errors in your Career & Education History.
January 12, 2026 at 2:03 PM
olivia.science
"baby eating bishop of bath and wells" ass but yes it is 100% but I do have them all
Boxset of Blackadder the complete collection
January 12, 2026 at 8:53 AM
olivia.science
I did it. I hate streaming with a passion and I also apparently already have the Blackadder floors anyway. Got myself a belated Xmas present. 😌
Blu-ray dvd player box on the couch with remotes. Blackadder 2 dvd in the fancy coaster Projector showing the dvd menu which has the Blackadder 2 black and white tiles that match the ones on my floor.
January 12, 2026 at 8:46 AM
olivia.science
bsky.app/profile/oliv...

CC @andreaeyleen.bsky.social
So there are actually people that understand this kind of language? Because I don’t actually understand any of this. … ‪Olivia Guest · Ολίβια Γκεστ‬ ‪@olivia.science‬ · 1h To be a broken record, our paper isn't about how a term is murky per se. @andreaeyleen.bsky.social and I propose a metatheoretical solution to a theoretical problem. Esp see the parts we explain: success-to-truth inference & mechanism, in Boxes 1 & 2 & in the last section. bsky.app/profile/oliv... March 8, 2025 at 6:54 AM Everybody can reply
January 8, 2026 at 3:46 AM
olivia.science
I wrote a bit about it here bsky.app/profile/oliv...
Introduction [M]odels have to be used before they will give up their secrets. In this sense, they have the quality of a technology — the power of the model only becomes apparent in the context of its use. (Morrison & Morgan, 1999, p. 12) We are experiencing a point in history that considers itself separate, unique, a zenith of human civilisation, presented as disconnected from the past through a series of technological sea changes. In extreme cases, we are detached from even the last few months: the newest version of a piece of artificial intelligence (AI) software is the definitive one, everything else is irrelevant. And so findings in AI are held to expire. Our AI students describe their own knowledge and skills — even their whole degree itself — as having upcoming sell-by dates. Research in AI is thus often framed as unmoored from historical, ethical, social, and legal precedents. The speed of the “ultra rapid computing machine,” as Wiener (1948, 1950) de- scribes computers, becomes a metaphor for the speed of change and of techno- logical progress. This notion of condensed time operates as a further discursive regularity in two ways. First, it forms an overall temporal backdrop against which various cybernetic dramas are played out. Second, condensed time becomes a measure of the performance of humans and machines. Hughes (1985) offers a telling example of the first manifestation of condensed time: In the scant two hundred years since the early Industrial Revolution, Western man has totally rescaled and changed the face and fabric of his environment. Indeed, the changes have proceeded at such an acceler- ated pace that we might use the word “old” or “outmoded” to refer to last month’s computer model. (p. 205) 1 O. Guest This sense of condensing time—of speed, of rapid change—imbues virtually all the popular literature examined. It becomes a contextual operator, stated but not questioned. (Hamilton, 1998, p. 193) What Sheryl N. Hamilt…
January 7, 2026 at 5:48 AM
olivia.science
"Great man theorising requires the (re)orientation of the theory to direct all credit to one person (or a biased subset of a select few) reminiscent of monarchy—far from the pluralistic or meritocratic facade science often hides behind"

doi.org/10.1007/s421...
Great Man Theorising Most of the work on women scientists fits the “history of great men” mold, with women simply substituted for men. Thus, we have many biographies of great women scientists. These biographical studies of women scientists, for the most part, place the achievements of Marie Curie or Rosalind Franklin within the male world, demonstrating that women have, in fact, made important contributions to what has been defined as mainstream science. Yet the focus remains on the woman as exceptional—the woman who defied convention to claim a prominent position in an essentially male world. One of the problems with this approach to history is that it retains the male norm as the measure of excellence. Londa Schiebinger, 1987, p. 314 On the one hand, it is common knowledge that scholarly activities are the fruit of the labour of teams of so-called great men’s students, mentees, collaborators, and partners. While on the other hand, the formal archival record gives a dramatically different account attributing such scientific outputs solely to individual men, and more recently individual people generally. To wit, great man theorising is ‘an important obstacle to building theory’ (van Rooij , 2021; also see van Rooij , 2022). Great man theorists fabricate and/or obscure anecdotal and historical evidence to ensure the credit is directed at the target prestigious figure. For example, Pythagoras is overwhelmingly named and credited, but he had many women disciples, who were philosophers and mathematicians in their own right, whose writings survive to this day, and after his death, Theano (a woman, possibly his wife) took over as head of his academy (Schiebinger, 1987; Wider, 1986). To give another example, Lavoisier, the chemist credited with discovering oxygen, was also a woman: Marie Anne Paulze Lavoisier. She could have been credited jointly with her husband, but was not (Eagle & Sloan, 1998). Great man theorising requires the (re)orientation of the theory to direct all credit to one person (or a biased subset of a select few) reminiscent of monarchy—far from the pluralistic or meritocratic facade science often hides behind—where few are in power and get credit, while many toil unseen (see Birhane and Guest , 2021, for more on how to deal with this). In reality, none of the research would be possible without all the laboratory members and students. Even if (in the unlikely case) the singular so-called great person is indeed generating all the ideas, the mental space they enjoy is only possible by the grace of their students, mentees, and employees.
December 30, 2025 at 8:46 PM