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Olivia Guest · Ολίβια Γκεστ

@olivia.scholar.social.ap.brid.gy
32 followers 2 following 276 posts

associate professor of computational cognitive science · she/they · cypriot/kıbrıslı/κυπραία · σὺν Ἀθηνᾷ καὶ χεῖρα κίνει 🌉 bridged from ⁂ scholar.social/@olivia, follow @ap.brid.gy to interact

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Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 16/09/2026
> Computational models in psychology are typically judged by a single standard: empirical fit. [However, it's] misleading as a sole criterion, as the same result can arise [in] different situations: theoretically faithful models, mathematically flexible ones, miscalibrated operationalizations […]
scholar.social
Original post on scholar.social
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Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 16/09/2026
RE: scholar.social/@olivia/112229979256… This is primarily based on and builds off work with @andrea from 2021, which discusses how computational models are (or can be) part of the way we perform our science. But it goes further and discusses how we can contextualise evidence for […]
scholar.social
Original post on scholar.social
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Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 16/09/2026
I'm excited to share this preprint by my wonderful MSc student Yihsin Chuang. She has thought deeply about how psychological & neurocognitive theories relate to different types of evidence. Beyond Empirical Success: Evaluating Theoretical Virtue Across the […] [Original post on scholar.social]
Beyond Empirical Success: Evaluating Theoretical Virtue Across the Computational Modeling Chain
Authors/Creators

    Chuang, Yihsin
    ORCID icon
    Guest, Olivia1
    ORCID icon

Description

Computational models in psychology are typically judged by a single standard: empirical fit. Unfortunately, fit is insufficient, even misleading as a sole criterion, as the same result can arise from fundamentally different situations: theoretically faithful models, mathematically flexible ones, miscalibrated operationalizations, or implementations that compute something other than intended. Distinguishing between these is vital. Our evaluative metatheoretical account recognises that models stand in three distinct relations: a) toward the theory whose causal commitments it purports to capture, b) toward the specification and implementation it purports to compute, and c) toward the phenomenon it purports to explain. Each relation can succeed or fail independently, governed by criteria local to that stage. Importantly, relations are ordered such that theoretical content is transmitted or lost, and losses at earlier transitions are irrecoverable downstream. What a model's empirical success implicates about its theoretical commitments, therefore, depends on whether transitions are secured. Some success or failure profiles support explanatory claims; others only prediction; others establish theoretical coherence without empirical contact. Our account diagnoses what a given model shows, replacing the implicit assumption that empirical success transfers automatically to theoretical understanding with an explicit conditional rendition of what models can and cannot establish.a figure that looks like a cloud that stays "cognitive capacity" with an arrow pointing to a lozenge with "theory" which points to a lozenge with "specification" which points to the same with "data" which is pointed to by a cloud that says "phenomenon"
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Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 16/09/2026
I'm excited to share this preprint by my wonderful MSc student Yihsin Chuang. She has thought deeply about how psychological & neurocognitive theories relate to different types of evidence. Beyond Empirical Success: Evaluating Theoretical Virtue Across the […] [Original post on scholar.social]
Beyond Empirical Success: Evaluating Theoretical Virtue Across the Computational Modeling Chain
Authors/Creators

    Chuang, Yihsin
    ORCID icon
    Guest, Olivia1
    ORCID icon

Description

Computational models in psychology are typically judged by a single standard: empirical fit. Unfortunately, fit is insufficient, even misleading as a sole criterion, as the same result can arise from fundamentally different situations: theoretically faithful models, mathematically flexible ones, miscalibrated operationalizations, or implementations that compute something other than intended. Distinguishing between these is vital. Our evaluative metatheoretical account recognises that models stand in three distinct relations: a) toward the theory whose causal commitments it purports to capture, b) toward the specification and implementation it purports to compute, and c) toward the phenomenon it purports to explain. Each relation can succeed or fail independently, governed by criteria local to that stage. Importantly, relations are ordered such that theoretical content is transmitted or lost, and losses at earlier transitions are irrecoverable downstream. What a model's empirical success implicates about its theoretical commitments, therefore, depends on whether transitions are secured. Some success or failure profiles support explanatory claims; others only prediction; others establish theoretical coherence without empirical contact. Our account diagnoses what a given model shows, replacing the implicit assumption that empirical success transfers automatically to theoretical understanding with an explicit conditional rendition of what models can and cannot establish.a figure that looks like a cloud that stays "cognitive capacity" with an arrow pointing to a lozenge with "theory" which points to a lozenge with "specification" which points to the same with "data" which is pointed to by a cloud that says "phenomenon"
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Reposted by Olivia Guest · Ολίβια Γκεστ
Pieter T. L. Beck @ptrbck.bsky.social · 29/08/2026
Investigative journalism outlet @apache.be , who were the first to discuss the topic of race science in Ghent, have translated their main articles to English apache.be/2026/03/05/s... /1
apache.be
Self-declared “race realist” Nathan Cofnas receives an appointment at UGent
American ‘woke’-fighter takes Maarten Boudry’s place.
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Reposted by Olivia Guest · Ολίβια Γκεστ
David Gerard @davidgerard.circumstances.run.ap.brid.gy · 14/08/2026
your next job could be in chatbot! could is such a great word www.gov.uk/government/news/ai-bootc…
gov.uk
AI bootcamp launched in north-west to combat youth unemployment
Young people out of work or at risk of entering unemployment after school are set to benefit from a first of its kind AI bootcamp kicking off in the north-west.
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Reposted by Olivia Guest · Ολίβια Γκεστ
David Gerard @davidgerard.circumstances.run.ap.brid.gy · 14/08/2026
at a loss for a hot AI story for today again, suggestions welcomed. what's pissing you off?
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Reposted by Olivia Guest · Ολίβια Γκεστ
[object Object] @zzt.mas.to.ap.brid.gy · 08/08/2026
@davidgerard this extends beyond Green, by the way. for more details on how ControlAI and other EA groups pay science communicators to push AI doom marketing, Carl from Internet of Bugs is excellent: www.youtube.com/watch?v=4lKyNdZz3Vw
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Reposted by Olivia Guest · Ολίβια Γκεστ
[object Object] @zzt.mas.to.ap.brid.gy · 06/08/2026
@davidgerard I’m very serious about this by the way if you respect science, you must not forgive hank green. you must spread the word on what he’s done, especially if you used to be a fan. this is corruption in the raw and what he’s done must be known. if you respect science, you must verify […]
mas.to
Original post on mas.to
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Reposted by Olivia Guest · Ολίβια Γκεστ
[object Object] @zzt.mas.to.ap.brid.gy · 06/08/2026
@davidgerard here’s David’s post with the YouTube video: circumstances.run/@davidgerard/1170… if you give a shit about truth and ethics in science communication and media, please show your friends who watch YouTube or TikTok or any of the other video sites what a shill […]
mas.to
Original post on mas.to
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Reposted by Olivia Guest · Ολίβια Γκεστ
[object Object] @zzt.mas.to.ap.brid.gy · 06/08/2026
hey so about your favorite boy hank green. it’s such a shame that he went overboard with the LLM stuff, that was impossible to see coming, good on him for realizing he was addicted right? well wishes for the good boy! anyway there’s smoking gun evidence that he was paid by effective altruists […]
mas.to
Original post on mas.to
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Reposted by Olivia Guest · Ολίβια Γκεστ
[object Object] @zzt.mas.to.ap.brid.gy · 08/08/2026
@davidgerard whether Green’s videos are marked as unsponsored because ControlAI paid him in one large lump sum with the understanding he’d do the rest of the AI videos, or it was an explicit part of a partnership contract, or Green’s a true believer fool who took a smaller sum for the sponsored […]
mas.to
Original post on mas.to
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Reposted by Olivia Guest · Ολίβια Γκεστ
[object Object] @zzt.mas.to.ap.brid.gy · 08/08/2026
@davidgerard for anyone unfamiliar with Yud: oh boy you don’t want it in short, Yudkowsky invented the modern, AI doom cultist, capital-R form of Rationalism. without Yud and Soares, the TESCREAL belief package wouldn’t have the shape or the political power that it does now. these are core […]
mas.to
Original post on mas.to
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Reposted by Olivia Guest · Ολίβια Γκεστ
[object Object] @zzt.mas.to.ap.brid.gy · 08/08/2026
@davidgerard Green stated that he did this in order to present a variety of views on AI, but that’s not true. all of the interviews and AI videos on Green’s channel are in support of ControlAI’s AI doom narrative. there are no opposing viewpoints challenging the ridiculous and unscientific idea […]
mas.to
Original post on mas.to
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Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 04/08/2026
💥 Mass action against data centres on November 6 in Amsterdam 💥 More info here: linktr.ee/geeftegengas www.instagram.com/geeftegengas
an image with a group of people in kufiyas facing away from the camera 

in light green text it says: 

JOIN US FOR OUR MASS ACTION 

November 6 
Amsterdam

RISE UP AGAINST DATA CENTERS 

TELEGRAM CHAT VIA THE LINK IN BIO
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Reposted by Olivia Guest · Ολίβια Γκεστ
Mario Munoz @pythonbynight.hachyderm.io.ap.brid.gy · 06/08/2026
@yoginho I would probably take a look at this open letter, as well as some of the respondents on this post. It centers on Academia, but there may be some threads to follow there that overlap: scholar.social/@olivia/117036188700…
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Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 04/08/2026
Open Letter: Stop the Uncritical Adoption of AI Technologies in Academia It's been a year & people tell me they've changed their mind, feel safer now to sign, etc. So I'm sharing it again for them. We're almost at 2k & anybody from anywhere can add their […] [Original post on scholar.social]
We call upon you to:

* Resist the introduction of Al in our own
software systems, from Microsoft to OpenAl
to Apple. It is not in our interests to let our
processes be corrupted and give away our
data to be used to train models that are not
only useless to us, but also harmful.

+ Ban Al use in the classroom for student
assignments, in the same way we ban essay
mills and other forms of plagiarism. Students
must be protected from de-skilling and
allowed space and time to perform their
assignments themselves.
+ Cease normalising the Al 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.

* Fortify our academic freedom as university
staff to enforce these principles and
standards in our classrooms and our research
as well as on the computer systems we are
obliged to use as part of our work. We as
academics have the right to our own spaces.

+ Sustain critical thinking on Al and promote
critical engagement with technology on a firm
academic footing. Scholarly discussion must
be free from the conflicts of interest caused
by industry funding, and reasoned resistance
must always be an option.
0646
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 04/08/2026
💥 Mass action against data centres on November 6 in Amsterdam 💥 More info here: linktr.ee/geeftegengas www.instagram.com/geeftegengas
an image with a group of people in kufiyas facing away from the camera 

in light green text it says: 

JOIN US FOR OUR MASS ACTION 

November 6 
Amsterdam

RISE UP AGAINST DATA CENTERS 

TELEGRAM CHAT VIA THE LINK IN BIO
017
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 04/08/2026
Open Letter: Stop the Uncritical Adoption of AI Technologies in Academia It's been a year & people tell me they've changed their mind, feel safer now to sign, etc. So I'm sharing it again for them. We're almost at 2k & anybody from anywhere can add their […] [Original post on scholar.social]
We call upon you to:

* Resist the introduction of Al in our own
software systems, from Microsoft to OpenAl
to Apple. It is not in our interests to let our
processes be corrupted and give away our
data to be used to train models that are not
only useless to us, but also harmful.

+ Ban Al use in the classroom for student
assignments, in the same way we ban essay
mills and other forms of plagiarism. Students
must be protected from de-skilling and
allowed space and time to perform their
assignments themselves.
+ Cease normalising the Al 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.

* Fortify our academic freedom as university
staff to enforce these principles and
standards in our classrooms and our research
as well as on the computer systems we are
obliged to use as part of our work. We as
academics have the right to our own spaces.

+ Sustain critical thinking on Al and promote
critical engagement with technology on a firm
academic footing. Scholarly discussion must
be free from the conflicts of interest caused
by industry funding, and reasoned resistance
must always be an option.
0646
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 03/08/2026
RE: scholar.social/@olivia/117026104474… I forgot to address one type of person: those who say "don't care so much, if you can, since it makes you sick" — I hear you, and I will ask you this: don't stand in our way when we fix this and don't claim you helped when you just told us […]
scholar.social
Original post on scholar.social
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Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 02/08/2026
@theluddite oh, yes, very good piece. Also see this piece on this awful fascist nonsense too: > The genocide against the Palestinian people should make Israeli scientists uncomfortable. It should make all Israelis uncomfortable, as it should make all people, all moral actors uncomfortable. It […]
scholar.social
Original post on scholar.social
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Reposted by Olivia Guest · Ολίβια Γκεστ
The Luddite @theluddite.assemblag.es.ap.brid.gy · 02/08/2026
@olivia Read, and I feel similar anxiety. The first night of the conference, I slept very poorly, instead thinking over many of the intellectual train wrecks I had just experienced. I would ask simple questions about conceptualizations (e.g., doesn't your definition of "harmful content" include […]
assemblag.es
Original post on assemblag.es
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Reposted by Olivia Guest · Ολίβια Γκεστ
The Luddite @theluddite.assemblag.es.ap.brid.gy · 02/08/2026
@olivia Also, good lord that quote from Abdaljawad Omar is sharp. Stashed away for future reference! (3/3)
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Reposted by Olivia Guest · Ολίβια Γκεστ
The Luddite @theluddite.assemblag.es.ap.brid.gy · 02/08/2026
@olivia To add to your point on ceding academic institutions, I come to my PhD in my late 30s, after 15+ years of organizing. I've had the immense privilege of seeing victorious labor actions by exploited, wildly underprivileged workers. By contrast, academic institutions give workers so much […]
assemblag.es
Original post on assemblag.es
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Reposted by Olivia Guest · Ολίβια Γκεστ
The Luddite @theluddite.assemblag.es.ap.brid.gy · 02/08/2026
@olivia I'm a simple man. I see my favorite Marx quote and I boost. I invoked this very quote just recently in response to this comically stupid peer review comment: assemblag.es/@theluddite/1169695428… So much for the ruthless criticism of all things 🫠
assemblag.es
The Luddite (@theluddite@assemblag.es)
One of the peer reviewers who rejected this paper put it best, so we will give them the last word on this thread: >The authors' comments about the MBFC scores reflecting the "common idea of the liberal media" miss the Okkam's [sic] Razor solution that this is in fact the distribution of bias of media outlets.
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Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 02/08/2026
If useful, here's my attempt to process my feelings about how I feel sadly kinda — or rather very — sick from all this AI fascist nonsense as an academic. 😶‍🌫️ I'd be pleased if even one person finds something useful because there's something to be said for processing this all together, so, um […]
scholar.social
Original post on scholar.social
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Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 01/08/2026
Glad this is coming out because this stank to high heavens for years. I had Buck blocked on twitter for ages. @davidgerard circumstances.run/@davidgerard/1170…
circumstances.run
David Gerard (@davidgerard@circumstances.run)
> One of the reviewers who seemed too close to the issue called it “unseemly” and “inflammatory” to talk about the central role and beliefs of private philanthropists funding open science. https://scatter.wordpress.com/2026/07/31/science-funding-and-the-cherry-picking-problem/
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Reposted by Olivia Guest · Ολίβια Γκεστ
David Gerard @davidgerard.circumstances.run.ap.brid.gy · 01/08/2026
> One of the reviewers who seemed too close to the issue called it “unseemly” and “inflammatory” to talk about the central role and beliefs of private philanthropists funding open science. scatter.wordpress.com/2026/07/31/sc…
scatter.wordpress.com
science funding and the cherry picking problem
Science publishing–like all of science–requires money. There’s no getting around it, even with the open science movement. What appears free to many authors and readers still requires money and infrastructure. Popularizing the open science movement cost money, too. I tried to talk about where that money came from in my new paper with Molly King, but that part of the paper was censored. One of the reviewers who seemed too close to the issue called it “unseemly” and “inflammatory” to talk about the central role and beliefs of private philanthropists funding open science. After multiple rounds of review where we demonstrated the reviewer was wrong about basic facts such as the names of donors and the amounts of money, they retreated to their core claim: discussion of funders and motives “doesn’t belong” in a paper about feminist ethical considerations and open access publishing.1 Our paper’s acceptance was made conditional on cutting it. I think it’s too important not to share. Two years ago, when we were writing the paper, I worried that the way open science was funded left the door open to far-right, anti-science co-optation. We speculated that it opened the door for wealthy, anti-science, anti-woke interests to undermine science. During the revision process, my fears began coming true. Today, we have a new “gold standard science” initiative coopting science reform rhetoric, and some of the same players we discussed are involved in the Trump administration’s efforts to undermine science. I should start with **some caveats**. This section of the paper was my pet project; my coauthor was along for the ride. This post, too, is my own, although of course we discussed it. I bear no ill will toward the editors or the reviewer who demanded we cut the section. They were very knowledgeable about open science, and the paper is genuinely better as a result of their feedback on other parts of it. Understandably, people get sensitive when someone suggests their work may be funded or cited for nefarious purposes, even if they themselves are virtuous. It is not a pleasant possibility to consider. Indeed, it was “ruining an otherwise reasonable and interesting paper” for the reviewer. Nor is there any purity politics here: I use the same open science infrastructure we wrote about, and I have taken money from billionaires whose politics I don’t agree with. As Philip Cohen rightly pointed out in a bluesky conversation, with the cuts and censorship in federal funding, private philanthropy may be increasingly important for science. I take to heart Donna Haraway’s point that there is no way to live and also keep our hands clean.2 Instead, I want to make two points. The first is the reality of how science reform got so popular. John Arnold dumped tens of millions of dollars on a few academics with heterodox views, which catapulted them to fame and influence. When and why powerful and wealthy outsiders chose to pluck scholars and ideas from obscurity should be of key concern to those of us interested in the independence of science. And second, I want to suggest there are better and worse ways to organize science funding, which will always depend on political or monied elites. We can’t have clean hands, but we can be honest with ourselves and deliberate with our choices. **Arnold’s** **influence** is undeniable. (Sorry, Reviewer A.) Two of the main academic figureheads for science reform, Brian Nosek and John Ioannidis, both give interviews saying their ideas had little traction until Arnold, the ‘Medici of meta-research’ as Ioannidis calls him, began funding them. Arnold gave money to Nosek to create the Center for Open Science (COS) and to Ioannidis to build the Meta-Research Innovation Center. He also funded Retraction Watch and other science reform projects that popularized the replication ‘crisis’ framing and cast doubt on the trustworthiness of science. This was not merely seed money. Arnold remained the single largest funder of COS every year until 2020. Even in 2022, the last year where COS finances were public3, The Arnold Foundation was contributing at least $1M annually, and their $23M in lifetime contributions accounted for 47% of all revenue COS had ever brought in. Arnold gave a lot of money. Wired reported more than $80M to “science critics and reformers” from 2012-2017. Stuart Buck, formerly the director of research at the Arnold Foundation (later Arnold Ventures), recounts allocating “over $60 million” of that. All of that money buys a lot of things. It pays for big, expensive replication studies that appeal to vanity journals like _Science_ and bring attention to the cause. It also buys things that feel more ‘unseemly,’ such as paying the first 1,000 scientists who would use their preregistration platform $1,000 each. Buck, a self-styled “metascience venture capitalist,” further takes credit for the money and his “active particip[ation]” in keeping organizations from going under, lobbying the federal government, instituting data and journal standards, and more. In the same substack post, Buck also takes credit for the scope of the vision: the foundation cold-called Nosek in 2012. Nosek didn’t seek them out, and initially his goal “was to get us to fund a post-doc position at maybe $50k a year.” A multi-million dollar center was the foundation’s idea. It’s hard to fathom a scholar turning down such an offer. **What motivates these investments?** Why did a hedge fund guy’s foundation take all this initiative to reach out to scholars and offer them immense resources they had not asked for? And then sustain them with tens of millions of dollars over the next decade? For insight into the Arnold Foundation’s motives, I’m relying on Wired’s interviews and reporting and Buck’s own retrospective account. They begin with Gary Taubes, a journalist with a masters in aerospace engineering and a best selling book claiming that the scientific consensus and government guidance about dietary fat was wrong. The foundation reached out to Taubes and gave him $40M in the first two years to found the Nutrition Science Initiative (NuSI). In Wired’s telling, Arnold heard Taubes on a libertarian podcast and reached out to offer him the resources needed to overturn scientific consensus. They paid a journalist to dig into the review process that led to federal dietary guidelines. That’s a good way to cast doubt on any finding, but not a particularly promising tactic for answering the substantive question about diets and health outcomes. (I’ll come back to NuSI in a bit.) After his positive engagement with Taubes, Arnold said he was convinced he could no longer trust any science unless he personally knew the researcher or vetted the work–he feared “the whole foundation of the research had been flawed.” And so Arnold began reaching out to other people who said science was untrustworthy and giving them money. The foundation cold-called and funded Ben Goldacre for his claims that “pharmaceutical companies, by refusing to reveal all their data, have essentially deceived the public into paying for worthless therapies.” Nosek got a call because of a _Chronicle_ article discussing his Reproducibility Project – then a volunteer crowdsource affair that the _Chronicle_ summarized as “We want to see how much of what gets published turns out to be bunk.” The article lionises Nosek as a brave challenger of the scientific establishment, opposed by internal forces who want to protect their own reputation and that of their field. Of course, “organized skepticism” is one of the four Mertonian norms of science. We’re supposed to scrutinize scientific work. And heterodox outsiders with views that challenge the scientific establishment are sometimes right (germs do cause disease, tectonic plates move, snake venom is a chemical substance, AIDS activists were right to demand changes in research, and so on). But there is something particularly dangerous to science, and particularly appealing to billionaires, about sweeping claims like Ioannidis’ that “most published findings are false.” They cast doubt not on a substantive fact about the world, which might be revised with better science, but on the authority of the scientific enterprise itself. Arnold made fortunes at Enron and then his own hedge fund, retiring at 35. As Wired tells it, Arnold believes traders have incentives to be correct: they make money when their bets are right. For successful traders like himself, their wealth is proof that they are intelligent and correct. The notion that ‘I’m rich, so I must be the smartest’ is a sort of secular prosperity gospel. Arnold worries that scientists have career and financial incentives to publish, which is not necessarily the same as being correct. So he wants to remake science with ‘better’ incentives (i.e. in his own image). (Most scholars I know want to be correct not for the sake of our careers, but because we care about the things we work on, whether that’s finding a cure for cancer or understanding pathways out of poverty. But passion, altruism, and curiosity are hard to frame in the language of ‘incentives.’) **A lot of good** has come from one billionaire deciding to make science reform his pet cause. Some fields prone to especially small and WEIRD samples are thinking more about sampling. And there has been a huge growth in open access publishing, data, and code (although my paper with Molly shows that growth is uneven, and openness is not always good or possible). But **there is a lot of danger** , too, in allowing the whims of the world’s wealthiest or most politically powerful individuals to cherry pick scholars or ideas out of relative obscurity and catapult them into major movements.4 We wrote initially that the funding model was open to actors with worse views than Arnold. Peter Thiel also believes science is “very, very diseased,” too hostile to heterodox views, and devoid of finance industry style incentives. It would not be hard for him to spend tens of millions of dollars on his pet science reforms (ending ‘wokeness’ in his case). The reviewer did not see the relevance–Thiel wasn’t funding science reform at the time. Now, of course, Thiel does not need to. The Trump administration is using federal funding to push that agenda, with Thiel’s former chief of staff as the new head of the Office of Science and Technology Policy. Cooptation of science reform for dubious ends is not new or impossible to anticipate. The tobacco industry leveraged the virtues of open science to discredit research on lung cancer (they argued the research was untrustworthy, because the medical records used as data were confidential). For many of the world’s political and economic elite, science represents an outside authority challenging their own interests (consider climate change, vaccines, _& c_.). It is easy to imagine why some of them would want to promote scientists saying science is untrustworthy. **Where are we now?** Stuart Buck, for his part, is now executive director of a related initiative and writes at length for a Trump-linked think tank in support of the “make American healthy again” agenda, claiming “NIH needs urgent reform.” He periodically gets pulled into social media fights over whether science on vaccines and climate change can be trusted. (He also opposed some Trump admin cuts.) NuSI did end up funding scientific research testing Taubes’ theory. Taubes got into a public fight over whether he tried to censor the study, which eventually published results showing Taubes was wrong. To their credit, the Arnold Foundation pulled out of NuSI after that. This is the primary risk of people outside science cherrypicking ideas or projects to fund that they find appealing. They can be wrong. Indeed, people with no expertise _will_ be wrong most of the time when they think they know better than a consensus of experts. Most heterodox ‘free thinkers’ are wrong or worse (reactionaries, quacks, grifters…). For his part, Taubes was invited to talk about his theory in an “NIH scientific freedom lecture” last month. Meanwhile, the scientist who discredited his theory recently quit the NIH, citing censorship. Scientists receiving this money don’t necessarily share or even know about their funders’ views. Brian Nosek and several other science reform figureheads have publicly criticized some aspects of the Trump administration’s science policy. In my own little corner of academia, most of the science reform advocates are strongly opposed to these politics. Our reviewer, who seemed very embedded in open science, did not know the vast scope of Arnold’s funding, which was several times more than the federal sources they thought made up the majority of COS’s total revenue. The editors suggested that the funding politics probably did not influence scholars’ behavior because “very few people are likely aware.” That seems right to me. It’s why I’m writing this. **A better way** is possible. It isn’t even particularly new. Philanthropists funding science can empanel a group of domain experts to solicit, review, and accept proposals. Domain experts are better positioned to know what work is promising, and to understand what the contribution of new research would be. Chemists should review chemistry proposals and so on. This is how the NSF, NIH, and other public funding agencies have long worked. It’s also how the Gates Foundation, Russel Sage, the Templeton Foundation, Schmidt Sciences, and others allocate much of their research support. It’s not perfect. I wish the economists Schmidt relies on were less narrowly focused on experimental designs, for example. But it is a strong compromise between funders’ interests and scholarly autonomy. Funders under this model still set topics and priorities–a disease they care about, a place that matters to them. And scientists are still asked to justify their importance to the public or the benefactor. Funders know what matters to them. But it is a tragic flaw of hubris to think they will pick the specific scholars or answers to scientific questions correctly. A panel of experts choosing the projects and people to fund insulates the whole system against several major risks. It prevents con artists and quacks from taking advantage of funder’s relative ignorance of the science. It prevents science as a whole from lurching wildly to chase whatever whim or fad catches the fancy of billionaires and politicians.5 And most importantly, it maintains faith in science as an enterprise, where organized skepticism is incorporated as an internal part of the truth-seeking process. Peer and editorial reviews are _brutal_ , at least in the sciences that still do them.6 I don’t have a solution to the cooptation of science reform by anti-science actors. More sober language than “crisis” from the reformers would be good, but it would not prevent motivated actions like we have seen in the last few years. The language of ‘crises’ and brave ‘heterodox’ outsiders challenging consensus is an effective way to draw in some philanthropists and politicians. But as any good metascientist should recognise: there are incentives here. To attract ‘metascience venture capitalist’ money or excite the current federal science leadership, it pays to make bold, sensational claims and discredit past work. Just as publishing is separate from getting things right, appealing to the desires and egos of economic and political elites is not necessarily aligned with doing careful, correct work of one’s own. 1. During the back and forth, we were asked to add discussion of the journal’s financial relationship with Sage for the sake of balance. I was happy to add it. An editor disliked having a discussion of how the professional organization Sociologists for Women in Society depends on revenue from Sage, but allowed it to remain, unlike the discussion of COS relying on money from Arnold. ↩︎ 2. Page 236 of _Manifestly Haraway_ has a compelling discussion of how it is impossible to be innocent and we should instead aim to be honest and deliberate about what we’re doing. She’s discussing ‘invasive species’ and killing animals in that passage, but the impossibility of innocent living is a broader theme of her work going back at least to the Cyborg Manifesto. ↩︎ 3. The finances were public at this OSF link, Nosek’s account. After we cited it to correct the reviewer, the document was taken offline and the link redirected to “forbidden.” The link to the Wired UK article we relied on also broke at this time. The coincidence was alarming. So I emailed Nosek, who sent back a friendly reply and attached a copy of the missing finance spreadsheets for me the next day. He also gave me permission to cite it as a personal communication from him. Cheers, Brian! It turns out that Wired did not take the story down, either, they just changed their URL structure from wired.com/article/john-arnold-bad-science to wired.com/story/john-arnold-bad-science. No conspiracies here, fortunately. ↩︎ 4. Most infamously, Jeffrey Epstein was well known for picking specific scholars and ideas to fund, often ones that fed into his own eugenic desires. I do not know of any connections between him and the other folks I write about here. This is an extreme case of the risk inherent to a setup where funders cherry pick the things that appeal to them most and shower them with money. ↩︎ 5. Again, Epstein comes to mind. ↩︎ 6. Most writing on peer review these days comes out of computer science, where conferences get 21,000 paper submissions and a majority of authors contribute to a free rider problem by shirking review duties. It is little wonder that AI ‘reviews’ are growing in popularity there. ↩︎ ### Share this: * Share on X (Opens in new window) X * Share on Facebook (Opens in new window) Facebook * Like Loading... ### _Related_ ## Author: Jeffrey Lockhart Jeff is starting as an assistant professor of sociology at UC Berkeley in Fall 2025. He skeets at jwlockhart.bsky.social . View all posts by Jeffrey Lockhart
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Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 18/07/2026
> I have a core take away I must repeat: just because somebody claims to be anti AI does not mean they are not doing entryism. Sadly, that is (in isolation) entirely consistent with entryism. Yes, these people lie about their beliefs. I repeat this quote from […] [Original post on scholar.social]
What can we do?

I have a core take away I must repeat: just because somebody claims to be anti AI does not mean they are not doing entryism. Sadly, that is (in isolation) entirely consistent with entryism. Yes, these people lie about their beliefs.

I repeat this quote from Marx that I put right at the top of our work critiquing this correlationist logic from 2023:

    "[A]ll science would be superfluous if the outward appearance and the essence of things directly coincided. (Marx, 1894, p. 592)" 

This is the logic of AI, of fascism, of sexism, of racism. That is, because things look a certain way, that therefore they are a certain way. Internal properties are wrongly derived from their superficial appearance. "I see that somebody has long hair, therefore I can conclude they are a woman." Or worse still: "I see the external features consistent with (what I think is) woman, and I conclude she must be stupid" — a fractal wrongness that starts with assuming that what you (naively, unquestioningly, think you) see is what you get when it comes to complex organisms. Further down in the same paper, we warn:

    "Just because a model correlates with neural and behavioral data, it is not sufficient for us to infer that the model is performing cognition: correlation does not imply cognition."

Again, the core logics of AI are the same as racism and sexism, which is why these issues pop up again and again in these systems: it involves taking the simple shallow features of things we see, like skin colour, or hair length, or whatever other superficial property, and moving to very flawed conclusions. There is something addictive to this form of sheer intellectual laziness — as well as structurally beneficial to those select few within capitalism, white supremacy and patriarchy — to this simplistic logic. It's easy to just point at people and call them names, I guess.
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Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 18/07/2026
Then you have to work on yourself also actually, because correlationism is very addictive: > There is something addictive to this form of sheer intellectual laziness [...] to this simplistic logic. It's easy to just point at people and call them names, I […] [Original post on scholar.social]
‘Just because a model correlates with neural and behavioral data, it

is not sufficient for us to infer that the model is performing cogni-

tion: correlation does not imply cognition."
Again, the core logics of Al are the same as racism and sexism, which is
why these issues pop up again and again in these systems: it involves tak-
ing the simple shallow features of things we see, like skin colour, or hair
length, or whatever other superficial property, and moving to very flawed
conclusions. There is something addictive to this form of sheer intellectual
laziness — as well as structurally beneficial to those select few within capi-
talism, white supremacy and patriarchy — to this simplistic logic. It's easy
to just point at people and call them names, | guess.
Non-human animals can escape from this correlationist logic. Think of the
animals who figure that out scarecrows, or other such fake predators, are
not alive. So even though first they may fear them similarly to their real
counterparts, animals realise that superficial resemblance is not identity:
"the outward appearance and the essence of things [have not] directly co-
incided" — a fake owl is not an owl. Correlationism is false.
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Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 18/07/2026
DO NOT turn it into demeaning / chastising those who slip up! > I am talking about those with immense power and those who consistently facilitate AI entryism being held to account. Nobody in the abstract is owed an audience nor do they deserve [...] being an […] [Original post on scholar.social]
| want to underline, people can make mistakes. Not everybody is know-
ingly using cultish language from industry, some still think these terms re-
fer. But notice who plows on regardless, who does not listen to feedback,
who materially and not just ideologically aligns with the Al companies. And
like with the case above from big P politics, once you see it, nothing the
person can do or say means they can return back to the table, or that they
can deserve an audience, or even that we owe them charitable readings of
their work. This is not about everybody who slips up being irredeemable.
These mistakes are normal. | am talking about those with immense power
and those who consistently facilitate Al entryism being held to account.
Nobody in the abstract is owed an audience nor do they deserve the ex-
tremely priviliged job of being an academic.
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Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 18/07/2026
OK, finally... > We must stop thinking that just because somebody agrees with us on some superficial anti AI point, that they are in fact in some deeper agreement on principles and values. Poor argumentation, like argument from ignorance or confusing […] [Original post on scholar.social]
We can't be anti Al if we don't make an effort to see these attempts at sub-
version. Entryism from industry is an extremely useful tactic, which still af-
fects and harms science in general, as well as Science specifically as we
see above. Regardless of how many times we try to root out the conflicts
of interest caused by Al they keep popping up like satanic mushrooms,
e.g. "Maples et al. find themselves part of a grotesque, predatory specta-
cle, laundering it with institutional credibility." And we live with the conse-
quences of how industry forces have successfully done this to harm cli-
mate science, to protect the tobacco industry and keep inserting it into the
scientific literature, and more.

If we are not careful with our reaoning about these events and learning
from the past, the same forces will act on us with respect to Al. Are petro-
leum companies good now because they also invest in renewables? Or do
they still owe the whole planet reparations?
001
Reposted by Olivia Guest · Ολίβια Γκεστ
Bastian Greshake Tzovaras @gedankenstuecke.scholar.social.ap.brid.gy · 27/07/2026
«Fluency-without-understanding is not a form of competence but its counterfeit. The willingness to work more slowly, more primitively, and more deliberately is the condition under which genuine capacity is built. The irony is that the same [tech] industry whose founding culture was organized […]
scholar.social
Original post on scholar.social
123
Reposted by Olivia Guest · Ολίβια Γκεστ
Bastian Greshake Tzovaras @gedankenstuecke.scholar.social.ap.brid.gy · 27/07/2026
«For much of the history of personal computing, hacker culture defined itself precisely by the deliberate refusal of convenience. The self-respecting programmer compiled from source, wrote her own tools, avoided proprietary dependencies, and regarded the ability to do things from first […]
scholar.social
Original post on scholar.social
116
Reposted by Olivia Guest · Ολίβια Γκεστ
David Gerard @davidgerard.circumstances.run.ap.brid.gy · 20/07/2026
we have an AI minister, and it's Some Fucker www.gov.uk/government/ministers/par… Kanishka Narayan, fresh meat from 2024 and nobody in particular the job is <small>AI safety</small> and <b><b>b<>***ONLINE […]
circumstances.run
Original post on circumstances.run
010
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 19/07/2026
There are more openly anti AI women than men, so if you see manels (panels of all men) or events where there are very few or no women involved on the academic speaking side (not in the organisation/teaching), it's safe to conclude that there is something very strange afoot to say the least […]
scholar.social
Original post on scholar.social
1315
Reposted by Olivia Guest · Ολίβια Γκεστ
Tael @tael.yiff.life.ap.brid.gy · 17/07/2026
RE: scholar.social/@olivia/116895347041… "When technology companies offer teachers and students ‘AI training’ or promote ‘AI literacy,’ they are engaged in brand marketing, framed as a progressive, philanthropically fundable intervention. The literacy label locates the problem in […]
yiff.life
Original post on yiff.life
001
Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 18/07/2026
@jonny relevant 💀 Pygmalion displacement 💀 doi.org/10.31235/osf.io/jqxb6
alion lens
1)  Feminised form: Is the Al, by its (default or exclusive) external characteristics, por- Yes/No
traying a hegemonically feminine character?
2) Whitened form: Is the Al, by its (default or exclusive) external characteristics, por- Yes/No
traying a character that is inherently white (supremacist), Western, Eurocentric, etc.?
3) Dislocation from work: Does the Al displace women from a role or occupation, or Yes/No
people in general from a role or occupation that tends to be (coded as) women’s work?
4) Humanisation via feminisation: Are the AI’s claims to intelligence, human-likeness Yes/No
or personhood contingent on stereotypical feminine traits or behaviours?
5) Competition with women: Is the Al pit (rhetorically or otherwise) against women in ~~ Yes/No
ways that favour it, and which are harmful to women?
6) Diminishment via false equivalence: Does the Al facilitate a rhetoric that deems Yes/No
women as not having full intellectual abilities, or as otherwise less deserving of per-
sonhood?
7) Obfuscation of diversity: Does the Al, through displacement of specific groups of Yes/No
people, “neutralise” (i.e., whiten, masculinise) a role, vocation, or skill?
8) Robot rights: Do the users and/or creators of the Al grant it (aspects of) legal per- Yes/No
sonhood or human(-like) rights?
9) Social bonding: Do the users and/or creators of the AI develop interpersonal-like Yes/No
relationships with it?
10) Psychological service: Does the Al function to subserve and enhance the egos of its Yes/No
creators and/or users?
002
Reposted by Olivia Guest · Ολίβια Γκεστ
jonny (nonvenomous) @jonny.neuromatch.social.ap.brid.gy · 18/07/2026
RealDoll the sex doll parent company bought by the roving husk of a cryptocurrency/metaverse capital demon pivots to selling hyper-realistic silicoid AI teaching robots to public schools on the Seneca Nation reservation, causing the state to spend $60k per doll they don't have to perform […]
neuromatch.social
Original post on neuromatch.social
3025
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 18/07/2026
OK, it's honestly very distressing and worrying and I have ADHD, so I wrote it all down to get it out of my head olivia.science/entryism Enjoy, I guess... > Now that being against AI in an informed way is becoming mainstream, we need to be aware of entryism: the long-term strategy […]
scholar.social
Original post on scholar.social
103
Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 10/07/2026
New preprint! So honoured to have worked with Ishani Ray on providing vital critique on "AI literacy" & correctives for those interested in understanding why "just use the newest version of an LLM" is nonsense Contra Literacy-Laundering: Mechanistic Critical […] [Original post on scholar.social]
Critical discourse on large language models (LLMs) has bifurcated between epistemic
dismissal that invokes some form of the stochastic parrot metaphor to puncture hype,
and pragmatic accommodation that treats LLM capability improvements as grounds for
updating the critique. We argue that both misdiagnose the problem as the issue is

not whether or not LLMs work, but what kind of working is happening and at whose cost.
Drawing on meta-theoretical frameworks of cognitive science, feminist labor analysis
and critical pedagogy, we propose a conceptual reorientation. We develop this claim
through registers of (i) the cognitive, examining what is forfeited when statistical pattern-
matching substitutes for the iterative, grounded processes that constitute thinking; (ii)
the pedagogical, examining how “Al literacy” as currently deployed is itself a symptom
of the confusion it purports to address; and (iii) the political, examining how the
infrastructure framing of Al naturalizes asymmetric labor displacement, particularly of
feminized cognitive and reproductive work. The stochastic parrot, deployed with
mechanistic precision rather than mere rhetorical convenience, specifies what is
forfeited when cognitive labor is delegated, who bears the cost, and why a literacy
adequate to this moment must begin from the epistemology of those most harmed by
the systems it describes. We conclude with underlining that critical Al literacy, which this
paper embodies an instance of, is the only sensible way forward.
2013
Reposted by Olivia Guest · Ολίβια Γκεστ
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 13/07/2026
> According to Van Rooij, the workshop suggests that using AI for writing is acceptable, smart and efficient. ‘And that is simply not true. Students or academics taking this course risk committing plagiarism. We are seeing a sharp rise in academic dishonesty amongst students using these […]
scholar.social
Original post on scholar.social
000
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 13/07/2026
> According to Van Rooij, the workshop suggests that using AI for writing is acceptable, smart and efficient. ‘And that is simply not true. Students or academics taking this course risk committing plagiarism. We are seeing a sharp rise in academic dishonesty amongst students using these […]
scholar.social
Original post on scholar.social
000
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 10/07/2026
New preprint! So honoured to have worked with Ishani Ray on providing vital critique on "AI literacy" & correctives for those interested in understanding why "just use the newest version of an LLM" is nonsense Contra Literacy-Laundering: Mechanistic Critical […] [Original post on scholar.social]
Critical discourse on large language models (LLMs) has bifurcated between epistemic
dismissal that invokes some form of the stochastic parrot metaphor to puncture hype,
and pragmatic accommodation that treats LLM capability improvements as grounds for
updating the critique. We argue that both misdiagnose the problem as the issue is

not whether or not LLMs work, but what kind of working is happening and at whose cost.
Drawing on meta-theoretical frameworks of cognitive science, feminist labor analysis
and critical pedagogy, we propose a conceptual reorientation. We develop this claim
through registers of (i) the cognitive, examining what is forfeited when statistical pattern-
matching substitutes for the iterative, grounded processes that constitute thinking; (ii)
the pedagogical, examining how “Al literacy” as currently deployed is itself a symptom
of the confusion it purports to address; and (iii) the political, examining how the
infrastructure framing of Al naturalizes asymmetric labor displacement, particularly of
feminized cognitive and reproductive work. The stochastic parrot, deployed with
mechanistic precision rather than mere rhetorical convenience, specifies what is
forfeited when cognitive labor is delegated, who bears the cost, and why a literacy
adequate to this moment must begin from the epistemology of those most harmed by
the systems it describes. We conclude with underlining that critical Al literacy, which this
paper embodies an instance of, is the only sensible way forward.
2013
Reposted by Olivia Guest · Ολίβια Γκεστ
Konrad Hinsen @khinsen.scholar.social.ap.brid.gy · 06/07/2026
New blog post: "Conviviality in computational science" blog.khinsen.net/posts/2026/07/06/c… "Conviviality matters for science for multiple reasons. One of them is epistemic: if you want to derive knowledge from your work, you need to know exactly what you are doing, and […]
scholar.social
Original post on scholar.social
5414
Olivia Guest · Ολίβια Γκεστ @olivia.scholar.social.ap.brid.gy · 18/06/2026
This is a full cleanse of your timeline and gorgeous zine doi.org/10.17613/afdz0-f6k56 > This collaborative zine emerged from a workshop on 4th June 2026 that gathered researchers and research professionals for a creative session around feminism and open research.
collage of text with green and red 

Fragments
of Rebellion
a
feminist
iSSUE
green background black text Bropen

'fuck off'

collageThis in reality version of open
science is the one I am primarily responding to, as it is the
version that has been elevated to an authoritative position in
psychology’s engagement with the open science movement 

As a qualitative and feminist researcher, I am concerned about 
the ways in which open science —and the elevation of it as the
solution for increasing rigor in psychological research 
threatens feminist epistemologies.
000