Furqan Shah

@shahfa.bsky.social

Assoc. Prof. @ University of Gothenburg 🇸🇪 #bone #biomaterials #osteocyte #osseointegration #biomineralization #bacteria #electronmicroscopy #Ramanspectroscopy 🦴🔬🦠🧪 https://linktr.ee/shahfa_

A major danger of LLMs is that humans are SO predisposed to attribute knowledge to any entity that uses natural language fluently. We cannot imagine that a machine that outputs natural-seeming speech/text doesn't have cognition. Brilliantly articulated by @emilymbender.bsky.social et al. (2021).

Text generated by an LM is not grounded in communicative intent, any model of the world, or any model of the reader’s state of mind. It can’t have been, because the training data never included sharing thoughts with a listener, nor does the machine have the ability to do that. This can seem counter-intuitive given the increasingly fluent qualities of automatically generated text, but we have to account for the fact that our perception of natural language text, regardless of how it was generated, is mediated by our own linguistic competence and our predisposition to interpret communicative acts as conveying coherent meaning and intent, whether or not they do [89, 140].”
Kat Tenbarge@kattenbarge.bsky.social · last yr.

It’s a hard pill to swallow but people really do trust ChatGPT as a definitive source of authority. Not everyone. But enough that this week I saw a ChatGPT quote on a subway ad and a salesperson told someone next to me they could ask ChatGPT their question and get the same answer

🧪 The peer review system is truly broken! 😵‍💫 An editor's perspective: –Ever increasing number of manuscripts submitted for publication –Authors want quick editorial decisions + fast peer review –Reviewers are "too busy" to review –Everyone wants to submit papers but no one wants to review 1/2