mastodon 4.7.3associate professor of computational cognitive science · she/they · cypriot/kıbrıslı/κυπραία · σὺν Ἀθηνᾷ καὶ χεῖρα κίνει
Like with entryism & related sabotage, it's easy for experts to spot. I explained how at the top.
Is it intentional? You can decide:
who plows on regardless, who does not listen to feedback, who materially and not just ideologically aligns with the AI companies.
https://olivia.science/entryism/
4/n
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
https://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 deployed by pro AI people or entities, like companies, to subvert such movements.
1/n
> The controversy associated with the statement “Ada Lovelace was the first computer programmer” reveals more about modern attitudes towards women [than her] achievements. [Her 1843 algorithm] was so advanced, that it was still utilised in record-breaking computation of Bernoulli numbers in 2008.
https://blue-stocking.org.uk/2024/06/14/ada-lovelace-the-first-computer-programmer/
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.
4/
@samhforbes@scholar.social and I:
> LLMs are labor intensive, are economically infeasible, and pollute the environment, and these properties may outweigh any proposed benefits. For example, poor quality air directly harms human cognition, and thus has compounding effects on educators' and pupils' ability to teach and learn.
To Improve Literacy, Improve Equality in Education, Not Large Language Models https://doi.org/10.1111/cogs.70058
Anyway, back to the work itself (from the abstract):
Critical discourse on large language models (LLMs) has bifurcated between epistemic dismissal [...] and pragmatic accommodation that treats LLM capability improvements as grounds for updating the critique.
https://doi.org/10.5281/zenodo.21222978
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Touched grass today, but the cool kids were eating it
If a guy named Geoffrey Jefferson can figure this out in 1949...
"The mind of mechanical man." British Medical Journal
https://doi.org/10.1136/bmj.1.4616.1105
1/
Or to put it a different way: Why do we tolerate these claims? And even accept them as excuses? Or as a new normal?
The dramatic irony here is [that companies and scientists] are willing to go on record saying they do not know how these models work @CyberneticForests@assemblag.es
https://doi.org/10.5281/zenodo.20071869
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Thank you to all who did the translating of our Open Letter: Stop the Uncritical Adoption of AI Technologies in Academia — can't believe we have: Brazilian Portuguese, Dutch, French, German, Italian, Spanish 💥‼️
✍️ sign here: https://openletter.earth/open-letter-stop-the-uncritical-adoption-of-ai-technologies-in-academia-b65bba1e?limit=0
🌏 all languages here: https://olivia.science/ai/#activism
To address these confusions, we must consider how:
In a world where the technology industry and even our colleagues reject theory building, through ignorance, mockery, and semantic shell games, we can subvert their feigned lack of understanding to our advantage. Scientific theorising has more not less value in times of scarce deep thinking, thought-less technosolutionism, and obfuscation of the cognitive.
https://doi.org/10.5281/zenodo.20071869
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The stochastic parrot [...] 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.
https://doi.org/10.5281/zenodo.21222977
6/
reminder...
> Anybody can ‘win’ a marathon if driven by car. Does that make it a weakness of the marathon race as an endurance event? Or does it reflect a deeper category error on our behalf, like with the misapplication of statistical tests, that an assumption has been violated?
This is the issue with theoretical work these days. Data isn't collected as means unto itself unless we've lost the point of experiment & observation. Without explicit theory to house data it's meaningless. Duhem-Quine, underdetermination of theory of by data is lost on people.
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Published!
What Does ‘Human-Centred AI’ Mean? https://doi.org/10.3390/bs16040583
Thank you to Andy Wills https://www.andywills.info for inviting me to his SI (Advanced Studies in Human-Centred AI) — and furthermore, for being up for me completely disagreeing with so many mainstream views on HCAI! Great reviews too.