Comment by ACCount37
17 hours ago
I don't think cognitive linguistics has that much to say about AI nowadays. Let alone philosophy.
The biggest contributions from linguistics are probably "human languages mostly have statistical regularities rather than hard rules" and "the sum of data humans get from birth to language acquisition is insufficient to learn a language from scratch". Which LLMs already work with, and work around, respectively. From there, nothing.
And philosophy just exists to be a distractor. "Subjective experience" is too subjective to matter in practice. "Task performance" is measurable, "consciousness" isn't. "Agency" is something an LLM in a tool calling loop, a rat in a maze and a human in an office tower may or may not have, depending on your favorite definition. Agentic LLMs are years in the making, and that's a product of engineering, not philosophy: "agentic" is whatever gets the job done.
We are yet to discover any physical process whatsoever that can't be represented as mathematical operations and implemented by a Turing machine. So all of that "treating human mind as a machine is wrong" amounts to "human mind must be powered by magic fairy dust" paired with "a functionally similar magic-free replacement is impossible". I'm not about to give much weight to any hypothesis that requires undiscovered magic fairy dust. At least find the hyper-computational magic fairy dust first - not just assume it absolutely must be there because you want the human mind to be unique and special.
Want to know why Turing did what he did? It's because he didn't want to engage with any of that "what is mind" bullshit either. So he proposed actual metrics - measurables that are harder to argue in circles about. Not that it stopped anyone. But at least he tried.
> I don't think cognitive linguistics has that much to say about AI nowadays. Let alone philosophy. I would like to read those sources.
> The biggest contributions from linguistics are probably "human languages mostly have statistical regularities rather than hard rules" and "the sum of data humans get from birth to language acquisition is insufficient to learn a language from scratch". Which LLMs already work with, and work around, respectively. From there, nothing.
Again, what's the source for 'biggest contributions from linguistics are...'? It is a big contribution to the development of LLMs, but different cognitive linguistics authors already challenged this idea already 20-30 years ago. LLMs work with and around the problems you cite because of massive data/money, not at the fundamental level. It is all a game of statistics and data, which has been already challenged by cog. ling.
> And philosophy just exists to be a distractor. Well, this is just telling me that you either know too much about philosophy and reached that conclusion (which might make sense, know of some philosophers who also think that) or you just read too little.
> So all of that "treating human mind as a machine is wrong" amounts to "human mind must be powered by magic fairy dust"
This is the common fallacy people in AI/IT make . One of the benefits of reading philosophy is that you find your way out of them.
> Want to know why Turing did what he did? The actual tests Turing though about are themselves flawed (not that I discovered that, has been known for some time already)
Again: either stop using > quotes or learn to use them better. Fucking unreadable.
I reiterate: philosophy is almost entirely worthless for AI design. We want to design systems that work, not systems that sound good on paper. If philosophy had a practical application in that, we'd stop calling it "philosophy" and start calling it "math", "science" or "engineering".
Again: don't be rude. Not nice. As 'not nice' as my bad formatting.
Philosophy is there precisely to critique and analyze what we build and how we behave in the world. Without it, by the way, there would be no science and no engineering.
Dismissing philosophy in AI is like dismissing philosophy in any other applied, practical or creative field. It is precisely because there is a philosophical investigation on each practical, applied or creative field, that that field can actually make progress.
There's philosophy in biology, which helps biology go further. Philosophy in engineering, which makes engineering go further. In architecture, film, photography, painting, literature, medicine, physics, linguistics, mathematics, etc, etc. In all those fields, there is also a philosophical investigation taking place. Right now.
Maybe you confound practical AI design (you should be talking of 'building AI systems') with AI as a research field. I get that, because lots of people cannot make the distinction (calling yourself 'AI researcher' when you actually tinker a model is not scientific. It might follow a scientific method, but it is engineering research, not scientific research).