That's the issue right there, I would also argue. And this epistemology thing is at the heart of the whole (AI) post-truth phenomenon.
You know, people often belittle philosophy as a useless field, and for some fields and subjects they are very right in that (witness all the arguments over finitism or existential inertia), but I think there are a few fields of philosophy that are actually really important. Not because they give answers, but because they give you a larger, richer, and consequently more nuanced tool set with which to approach certain categories of problems that are otherwise difficult to think about, or even notice as problems in the first place, by giving you access to a whole history of thought. In this respect I think philosophy of mind, epistemology, language, semiotics, and to a lesser extent ethics have crucial bearing on the things we see happening nowadays, including the advent of large language models. It's frustrating as someone who's really interested in philosophy to see people discuss these things where long history of philosophical thought is relevant without any real respect for or experience in those fields. It leaves their arguments often reductionist and/or bereft of strong argument and clear reasoning, full of implicit assumptions and ignored details, even when they're right.
Whenever I hit that brushes up against these, I always find myself wishing that introductions to these topics were more easily found. I’m not saying they don’t exist, just that there’s no clear entry point to start learning about the philosophy of mind (or others). It’s like in Math, where you have books like Lang’s “Algebra” which are titled in the most literal way possible. It is simultaneously exactly what’s in the book, but woefully inappropriate for people who don’t already know what it is.
Do you have any recommendations?
Basically, try to find books that are composed entirely of the juicy sections of primary sources on a given subject from all sorts of different points of view, preferably with some footnotes and introductions to give proper context. Not handbooks or something where it's content by many authors, but written for the occasion — stuff made of primary sources. Things like this[0], although I haven't read that particular specimen since most of the ones I read to get into philosophy were bespoke ones made by my professors. Also, the Stanford Encyclopedia of Philosophy is indispensable for getting a real sense for the philosophical debate about any given topic — the arguments back and forth in all their minutae. Also have Wikipedia handy for definitions of technical jargon (always read the "criticism" or "responses" sections! and also remember Wikipedia is often incomplete).
In my opinion then the general point is that to become familiar with, and even good at thinking and arguing about, even rather deep philosophy, you don't necessarily need to sit down and munch through a dense and possibly dull primary source or didactic textbook from cover to cover unless you want to. Engaging with primary sources is good, but doing so when and where it seems interesting, on your own terms, in bite sized chunks, with secondary sources to supplement and broaden your horizons, is more likely to avoid burnout and help you digest things, so it's better in the end.
Also, I highly recommend Philosophical Investigations, it's very good and reasonably accessible from what I've read of it.
[0]: https://www.amazon.com/Analytic-Philosophy-Anthology-P-Marti...
Plenty, but it's complicated. I've been thinking about these ideas a lot:
> The historical claim is that in the last decades, we have seen an overreach of the logic of markets, with markets being defended precisely for their capacity to deal with decentralized knowledge.
Phew, I never really drew the parallel between the current bane of my existence (the trust in the almighty algorithm and the perceived objectiveness of anything with numbers in it regardless of their ability to actually describe the supposed phenomena; okay parenthetical rant stopping early) and the “trust in the market.” But I’ll be damned if I’m ever going to not make it now. I really want to talk at length about how we (machine learning practitioners) have made our own beds with people jumping to conclusions about higher order reasoning and the ability to recall anything used in a training set by being militant about that separation as individuals but failing miserably as communities; and I want to talk about how that has created this perception of exactly what she’s referring to: over-leveraged trust in diffuse, “decentralized” knowledge. But… I won’t. At least not yet.
I’m going to check this book out. Thanks for the recommendation!
No problem. I think it is quite brilliant in many ways, although, of course, not in everything. As for us technologists and engineers, see particularly Section 8, although there are plenty of relevant bits and pieces elsewhere too.