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> I highly recommend people in the AI research space should read philosophy and modern linguistics. On the contrary, I highly recommend people in Philosophy of
by ozgung 5mo ago
> I highly recommend people in the AI research space should read philosophy and modern linguistics.
On the contrary, I highly recommend people in Philosophy of mind and linguistics should start reading AI research papers because their theories and ideas are highly outdated, even ancient. Your books are from 1927 and 1972 respectively and Turing's article is from 1950s. And they are relatively new with respect to other works in Philosophy.
If one doesn't adequately understand what we have in 2026, how can they theorize about it? As others they don't understand how the mind/brain work, BUT ALSO they don't understand how the AI works.
Also with this mindset that we can't understand seemingly complicated things, there would be no advancement in science and technology.
I think philosophy people and Linguist will catch up in a century, like they did with Turing. Philosophers of this century are not in humanities or literature. They are in science and engineering.
Heidegger was trained on priesthood and Theology. You should read greater minds like Hinton, LeCun etc. if you want to think on these things. They are the real Philosophers.
- Avicebron 5mo agoYikes dude. You may need to expand your horizons a bit.
- ozgung 5mo agoThat's my point. Everything from 1927 is already in plain sight and a part of the current public knowledge. Horizon can only be expanded at the cutting edges.
- jhonof 5mo ago> Horizon can only be expanded at the cutting edges. Ironically this was advice Ralph Waldo Emerson gave in 1840 so by your logic it's irrelevant just because it's old.
- f_klem 5mo ago> On the contrary, I highly recommend people in Philosophy of mind and linguistics should start reading AI research papers because their theories and ideas are highly outdated, even ancient. Your books are from 1927 and 1972 respectively and Turing's article is from 1950s. And they are relatively new with respect to other works in Philosophy. People in philosophy and cognitive linguistics do read AI research. Don't get fooled by the publishing dates: although Heidegger's work dates from 1927, the work is contemporary. The same happens with Dreyfus' work. Again, publishing dates don't mean anything here. Maybe you can clarify why they are outdated. > If one doesn't adequately understand what we have in 2026, how can they theorize about it? As others they don't understand how the mind/brain work, BUT ALSO they don't understand how the AI works. I would say that people involved in the critique of AI do know how it works. But I've found that is normally the case that people in AI research does not have the framing provided by works in philosophy or cognitive linguistics. > I think philosophy people and Linguist will catch up in a century, like they did with Turing. Philosophers of this century are not in humanities or literature. They are in science and engineering. What do you base your claims on? Plenty of philosophers work in humanities, literature, sociology as well as science and engineering. Philosophers not catching up? The critique on automation and AI already dates from the early 20s if not before. > Heidegger was trained on priesthood and Theology. You should read greater minds like Hinton, LeCun etc. if you want to think on these things. They are the real Philosophers. Sorry, but this does not make too much sense. Hinton and LeCun are great in their own fields. But seriously, they are not philosophers, they are inventors.
- ozgung 5mo ago> Maybe you can clarify why they are outdated. The First Edition (1995) of the classic textbook Artificial Intelligence: A Modern Approach by Russell and Norvig talks about the criticisms of Dreyfus quite extensively. In the second edition (2003) they conclude: "In sum, many of the issues Dreyfus has focused on-background commonsense knowledge, the qualification problem, uncertainty, learning, compiled forms of decision making, the importance of considering situated agents rather than disembodied inference engines-have by now been incorporated into standard intelligent agent design. In our view, this is evidence of AI's progress, not of its impossibility." In the 4th edition (2020) Dreyfus reduces to a paragraph and Heidegger is just a reference in a footnote.
- f_klem 4mo agoI have that book at home and I'll check as soon as I get back from a trip. When Dreyfus' book appeared in 1972, it received really harsh criticism from the then AI community. Dreyfus actually comments on that criticism in the revised 1992 edition. I just don't see how Dreyfus critique of AI has been dealt with in modern AI: the critique is aimed at fundamental issues, not at the technical issues. It is true that the critique written by Dreyfus is based on GOFAI algorithms from the 60s, but it is also true that if you read the book today, you'll find lots of similar situations and a similar way of thinking about the possibilities of AI, as well as the same underlying assumptions. And as a side note, outdated means that it does not apply anymore, or that is not relevant anymore. Which is different from 'establishing a dialogue' with the text/author, in a way that 'seems' not to be relevant anymore. If you say that Dreyfus' book is outdated just because the 4th edition of Norvig's text only mentions it in a footnote, you are assuming that Norvig and Russell's opinion are definitive. They might be not. I have authors like Norvig, Russel, LeCun, Minsky and other in the field in high regard. But they are normally not trained in either modern linguistics nor philosophy. Let alone the rest, large amount of researchers in the field. AI research is a complex field, and maybe (in this we could follow Foucault) not even a science. Doing research in an area of study does not turn it into science. It is precisely philosophy, and even more contemporary philosophy, the discipline that focuses on how we build knowledge, and how we experience the world. Two really important, almost fundamental, topics that directly contribute to how AI is developed as a field of knowledge.