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Lorraine Hope

@lorrainehope.bsky.social

Professor of Applied Cognitive Psychology at University of Portsmouth, UK. Special interest in memory performance and memory elicitation techniques. Views own.

43 Posts839 Follower 556 Folgt

Emily M. Bender @emilymbender.bsky.social · 3w ago

For ideas on how to do that, see: buttondown.com/maiht3k/arch... /fin

How to talk about "AI" without adding to the anthropomorphization

Emily M. Bender and Nanna Inie In our op-ed for Tech Policy Press ("We Need to Talk About How We Talk About 'AI'"), we made the case against the...

buttondown.com

The Irish Times @irishtimes.com · 5mo ago

Fearmhíniú (mansplaining), báinín (flat white) and other Irish words for modern life

As technology and culture evolve, the Irish language continues to generate new vocabulary

irishtimes.com

Lorraine Hope @lorrainehope.bsky.social · 5mo ago

Excited to have the opportunity to give this talk “High Stakes, Hidden Meanings: Culture, Memory, and Context in Investigative Interviewing” at #apls26 #apls2026 Looking forward to discussing the challenges and opportunities ahead!

Lorraine Hope @lorrainehope.bsky.social · 5mo ago

This is astonishingly brilliant! And basically a government information film 👏

Eiko Fried@eikofried.bsky.social · 5mo ago

The Norwegian Consumer Council with an amazing video on enshittification and how to resist it. www.youtube.com/watch?v=T4Up...

Olivia Guest · Ολίβια Γκεστ @olivia.science · 11mo ago

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

Sean Westwood @seanjwestwood.bsky.social · 9mo ago

AI presents a fundamental threat to our ability to use polls to assess public opinion. Bad actors who are able to infiltrate panels can flip close election polls for less than the cost of a Starbucks coffee. Models will also infer and confirm hypotheses in experiments. Current quality checks fail

Lorraine Hope @lorrainehope.bsky.social · 6mo ago

Hard recommend for the Mystery AI Hype Theatre 3000 Podcast - although you will end up sitting with your head in your hands, maybe crying a bit…

Emily M. Bender@emilymbender.bsky.social · 6mo ago

Mystery AI Hype Theater 3000 Episode 71, in which @alexhanna.bsky.social and I meet up for a “curb consult” and diagnose “A Bad Case of Hype-itis”: www.buzzsprout.com/2126417/epis... If only Big Tech were bound by the Hippocratic Oath.

Andrea Chittle MD MPH CCFP @andreachittle.medsky.social · 6mo ago

Imagine believing that using text-generating machines to perform clinical assessments & replace expert advice from real, qualified humans could improve health care. Such machines will deskill experts & surely kill. And you can bet the machines & their makers won’t be held accountable.

Emily M. Bender@emilymbender.bsky.social · 6mo ago

Jay Van Bavel, PhD @jayvanbavel.bsky.social · 6mo ago

Bureaucratic benchmarks are soul-crushing because they leave a big gap between what we care about and what can be measured. When we forget about the things we actually care about (like making interesting discoveries) and we write worse papers to get more publications, the metric eats the value.

ana gantman@anagantman.bsky.social · 6mo ago

Nguyen’s The Score & Nicholson Baker's A Box of Matches are a perfect set. The Score is about value capture (when metrics corrode their purpose) and Matches is about lighting a fire everyday and noticing stuff (i call it value release in the post) More here! anagantman.substack.com/p/bean-count...

Emily M. Bender @emilymbender.bsky.social · 6mo ago

If your study is framed as asking whether "AI" does X as well as humans do, it's fundamentally misguided and I'd argue not scientifically sound. A short 🧵>>

Margot Finn @eicathomefinn.bsky.social · 6mo ago

'to treat peer review as a throughput problem is to misunderstand what is at stake. Review is not simply a production stage in the research pipeline; it is one of the few remaining spaces where the scientific community talks to itself.' 1/3

AI is not a peer, so it can’t do peer review

If we still believe that science is a vocation grounded in argument, curiosity and care, we can’t delegate judgement to machines, says Akhil Bhardwaj

timeshighereducation.com

Damon Young @damonyoung.com.au · 6mo ago

I hate this. I hate that scholars and teachers are supposed to be digital fraud experts. I hate that this part of their job description is becoming larger and larger. I hate the widening distrust. I hate a culture that aggressively devalues the curiosity and humility required for ongoing learning.

Grumpy Philosopher@stevecooke.org · 6mo ago

New trick discovered today: an LLM-generated essay, saved as a PDF, with a tiny white space between each letter. This makes it impossible to paste quotes into a search engine, prevents text-matching in plagiarism checkers, & means URLs in bibliographies can't be clicked on. A lot of my time wasted.

Iris van Rooij 💭@irisvanrooij.bsky.social · 7mo ago

Will do a brief thread with highlights: “Many of our contemporaries now want to combine the worst of these two worlds [i.e., Psychology and Artificial Intelligence]. What could possibly go wrong? Quite a lot.” 2/🧵

Title page with abstract:

The current AI hype cycle combined with Psychology’s various crises make for a perfect storm. Psychology, on the one hand, has a history of weak theoretical foundations, a neglect for computational and formal skills, and a hyperempiricist privileging of experimental tasks and testing for effects. Artificial Intelligence, on the other hand, has a history of conflating artifacts for theories of cognition, or even minds themselves, and its engineering offspring likes to move fast and break things. Many of our contemporaries now want to combine the worst of these two worlds. What could possibly go wrong? Quite a lot. Does this mean that Psychology and Artificial Intelligence can best part ways? Not at all. There are very fruitful ways in which the two disciplines can interact and theoretically contribute to Cognitive Science, for instance, by studying the scope and limits of computational models of human cognition. But to reap the fruits one needs to understand how to steer clear of potential traps.

Sonja Drimmer @sonjadrimmer.bsky.social · 7mo ago

It is EXHAUSTING not only being made responsible for coming up with new kinds of assignments for our students; it's also tedious reading op-eds that suggest the core problem is a crisis in teaching. But, as Chris and I lay out here, this isn't a crisis in teaching; it's an attack on learning.

Sonja Drimmer@sonjadrimmer.bsky.social · 8mo ago

"We envision a resistance that is...a repudiation of the efficiencies that automated algorithmic education falsely promises: a resistance comprising the collective force of small acts of friction." "How to Resist AI in Education" by me & @cnygren.bsky.social www.publicbooks.org/four-frictio...

Nick Brown @steamtraen.eu · 8mo ago

Drake "Hotline" meme

Bad: Fabricating your participants

Good: Having Qualtrics fabricate your participants

Sabrina Norwood@sabrinanorwood.bsky.social · 8mo ago

Did you know that from tomorrow, Qualtrics is offering synthetic panels (AI-generated participants)? Follow me down a rabbit hole I'm calling "doing science is tough and I'm so busy, can't we just make up participants?"

Text reads: About synthetic panels
Recruiting the right participants for a study can be difficult. You may not get the exact demographics you need, and the shorter the deadline, the less sure you can be that everyone will answer on time. One possible solution can be to use synthetic panels.

Synthetic panels are powered by a first party proprietary AI model developed here at Qualtrics. Our synthetic panel is trained on thousands of responses from a variety of demographic backgrounds in order to more accurately predict how certain populations would respond to a survey.

Our synthetic panel is based on the United States General Population, and is only available in English. This panel comes with ready-made quotas and target breakouts in order to represent your chosen population and make it easy to launch your survey right away.

Lorraine Hope @lorrainehope.bsky.social · 8mo ago

The latest QRP (although it goes well beyond ‘questionable’ and straight into the realm of junk data fraud IMHO): LLM-hacking

Joachim Baumann@joachimbaumann.bsky.social · 8mo ago

Good luck drawing reliable conclusions from the answers that Qualtrics' AI model provides to your survey questions... bsky.app/profile/joac...

Joachim Baumann @joachimbaumann.bsky.social · 8mo ago

Good luck drawing reliable conclusions from the answers that Qualtrics' AI model provides to your survey questions... bsky.app/profile/joac...

Joachim Baumann@joachimbaumann.bsky.social · 11mo ago

🚨 New paper alert 🚨 Using LLMs as data annotators, you can produce any scientific result you want. We call this **LLM Hacking**. Paper: arxiv.org/pdf/2509.08825

$We present our new preprint titled "Large Language Model Hacking: Quantifying the Hidden Risks of Using LLMs for Text Annotation". We quantify LLM hacking risk through systematic replication of 37 diverse computational social science annotation tasks. For these tasks, we use a combined set of 2,361 realistic hypotheses that researchers might test using these annotations. Then, we collect 13 million LLM annotations across plausible LLM configurations. These annotations feed into 1.4 million regressions testing the hypotheses. For a hypothesis with no true effect (ground truth $p > 0.05$), different LLM configurations yield conflicting conclusions. Checkmarks indicate correct statistical conclusions matching ground truth; crosses indicate LLM hacking -- incorrect conclusions due to annotation errors. Across all experiments, LLM hacking occurs in 31-50\% of cases even with highly capable models. Since minor configuration changes can flip scientific conclusions, from correct to incorrect, LLM hacking can be exploited to present anything as statistically significant.$

Dr Abeba Birhane @abeba.blacksky.app · 8mo ago

I wrote this brief talk on why “augmenting diversity” with LLMs is empirically unsubstantiable, conceptually flawed, and epistemically harmful and a nice surprise to see the organisers have made it public synthetic-data-workshop.github.io/papers/13.pdf

title: Cheap science, real harm: the cost of replacing human
participation with synthetic data

author: Abeba Birhane

abstract: Driven by the goals of augmenting diversity, increasing speed, reducing cost, the
use of synthetic data as a replacement for human participants is gaining traction
in AI research and product development. This talk critically examines the claim
that synthetic data can “augment diversity,” arguing that this notion is empirically
unsubstantiated, conceptually flawed, and epistemically harmful. While speed and
cost-efficiency may be achievable, they often come at the expense of rigour, insight,
and robust science. Drawing on research from dataset audits, model evaluations,
Black feminist scholarship, and complexity science, I argue that replacing human
participants with synthetic data risks producing both real-world and epistemic
harms at worst and superficial knowledge and cheap science at best

Rolf Zwaan @rolfzwaan.eurosky.social · 8mo ago

Delighted to that my grant proposal with Anita Eerland, Verbs and Eyewitness Testimony: A Multilab Registered Replication Report, has been funded by @NWO (Dutch Research Council) through OpenScience.nl. Excited to get started on the project I describe here. rolfzwaan.substack.com/p/memory-mis...

Memory, Misinformation, and the Need to Replicate

Suppose you and a friend witness a car crash.

rolfzwaan.substack.com

Gordon Pennycook @gordpennycook.bsky.social · 8mo ago

🚨 Now out in Psych Science 🚨 We report an adversarial collaboration (with @donandrewmoore.bsky.social) testing whether overconfidence is genuinely a trait The paper was led by Jabin Binnendyk & Sophia Li (who is fantastic and on the job market!) Free copy here: journals.sagepub.com/eprint/7JIYS...

The Conversation UK @uk.theconversation.com · 8mo ago

Erasmus+ an accessible and well-supported programme.

UK to re-join Erasmus+ – here are six benefits of the European exchange scheme

Erasmus+ an accessible and well-supported programme.

tcnv.link

Dr Ian McCormick @wokestudies.bsky.social · 8mo ago

"an ever-widening gap between those who do the work and those who administer it. And an even larger gap exists between those tasked with most of the teaching and those who do most of the budgeting." www.aaup.org/underclass-s... #Highered #PhDchat #research #teaching #academicsky

The Underclass Is in Session

What do we see when we view the structure of academic labor as it is, not as we wish it to be?

aaup.org

Darren Dahly @statsepi.bsky.social · 2y ago

We know the drivers of research waste in academia are ⚠️Pressure to maximize papers and PhD students ⚠️Endless demands on time due to poor management ⚠️Stakeholders don't insist on robust quality systems to underpin mission critical work Solutions that don't address these are pointless.

Kathleen Bachynski @bachynski.bsky.social · 8mo ago

“Berg's point is that AI doesn't merely automate tasks — it automates the very processes through which people develop their skills.”

Olivia Guest · Ολίβια Γκεστ@olivia.science · 8mo ago

We can't really say this enough... > Anastasia Berg [at UCL Irvine] said that new research — and what she's hearing directly from colleagues across various industries — shows that employees who heavily rely on AI are losing core skills at a startling rate. www.businessinsider.com/ai-tools-are...

Katie Mack @astrokatie.com · 8mo ago

The most precious commodity you have is your attention. You don’t have to waste it on poor-faith debates or arguments with strangers if you don’t think they’ll be productive. You can prioritize the things that matter to you and make your life richer.

RedScharlach @redscharlach.bsky.social · 8mo ago

I feel you, ancient Mongolian ceramic hedgehog. I feel you.

A small cartoon version of the ceramic Mongolian hedgehog shown in the quoted post. Behind him is the word AHHH in very large lettering. The caption under him says "just keep screaming".

Oregon 🕎🎲@oregonthedm.bsky.social · 9mo ago

Part 218 of 200 in historically interesting things to inspire your ttrpg dnd Ceramic hedgehog dated to the Neolithic period found at the Hamin archaeological site near Shebotu Town in Inner Mongolia, China

Katie Mack @astrokatie.com · 9mo ago

It’s widely known (and, I think, pretty uncontroversial) that learning requires effort — specifically, if you don’t have to work at getting the knowledge, it won’t stick. Even if an LLM could be trusted to give you correct information 100% of the time, it would be an inferior method of learning it.

The Conversation U.S.@us.theconversation.com · 9mo ago

Relying on ChatGPT to teach you about a topic leaves you with shallower knowledge than Googling and reading about it, according to new research that compared what more than 10,000 people knew after using one method or the other. Shared by @gizmodo.com: buff.ly/yAAHtHq

Lorraine Hope @lorrainehope.bsky.social · 9mo ago

Absolutely this…there are still many predators evading their comeuppance, including in my own field.

Brian Nosek@briannosek.bsky.social · 9mo ago

There is so much to be disappointed about in this story--from the institutional response to Miles Hewstone himself. We still have a lot of work to do to make academic environments inclusive spaces where everyone can thrive, and where harassers are held accountable.

Josh McCrain @joshmccrain.bsky.social · 9mo ago

new paper by Sean Westwood: With current technology, it is impossible to tell whether survey respondents are real or bots. Among other things, makes it easy for bad actors to manipulate outcomes. No good news here for the future of online-based survey research

Andrew D Wilson @adw.bsky.social · 9mo ago

This seems bad on like 15 different fronts

Josh McCrain@joshmccrain.bsky.social · 9mo ago