Thanks! HN was part of the origin story of the book in question.
In 2018 or 2019 I saw a comment here that said that most people don't appreciate the distinction between domains with low irreducible error that benefit from fancy models with complex decision boundaries (like computer vision) and domains with high irreducible error where such models don't add much value over something simple like logistic regression.
It's an obvious-in-retrospect observation, but it made me realize that this is the source of a lot of confusion and hype about AI (such as the idea that we can use it to predict crime accurately). I gave a talk elaborating on this point, which went viral, and then led to the book with my coauthor Sayash Kapoor. More surprisingly, despite being seemingly obvious it led to a productive research agenda.
While writing the book I spent a lot of time searching for that comment so that I could credit/thank the author, but never found it.
That's one of the things that drives me nuts about all the public discourse about AI and our future. The vast majority of words written/spoken on the subject are by generic "thought leaders" who really have no greater understanding of AI than anyone else who uses it regularly.
A characteristic of the field since the beginning. Reading What Computers Can't Do in college (early 2000s) was an important contrast for me.
> A great misunderstanding accounts for public confusion about thinking machines, a misunderstanding perpetrated by the unrealistic claims researchers in AI have been making, claims that thinking machines are already here, or at any rate, just around the corner.
> Dreyfus' last paper detailed the ongoing history of the "first step fallacy", where AI researchers tend to wildly extrapolate initial success as promising, perhaps even guaranteeing, wild future successes.
And the article agrees with you, and is pretty scathing about all the books except Narayanan’s (which is also the only book with a balanced anti-hype perspective):
> A puzzling characteristic of many AI prophets is their unfamiliarity with the technology itself
> After reading these books, I began to question whether “hype” is a sufficient term for describing an uncoordinated yet global campaign of obfuscation and manipulation advanced by many Silicon Valley leaders, researchers, and journalists
Expert futurologist? Anyway. The article has very little substance. "See those ridiculous predictions," mostly. If there's anything about fundamental or practical limitations of the current machine learning approaches (deep learning, transformers, RL, and so on), I haven't seen it.
dang|5 months ago
randomwalker|5 months ago
In 2018 or 2019 I saw a comment here that said that most people don't appreciate the distinction between domains with low irreducible error that benefit from fancy models with complex decision boundaries (like computer vision) and domains with high irreducible error where such models don't add much value over something simple like logistic regression.
It's an obvious-in-retrospect observation, but it made me realize that this is the source of a lot of confusion and hype about AI (such as the idea that we can use it to predict crime accurately). I gave a talk elaborating on this point, which went viral, and then led to the book with my coauthor Sayash Kapoor. More surprisingly, despite being seemingly obvious it led to a productive research agenda.
While writing the book I spent a lot of time searching for that comment so that I could credit/thank the author, but never found it.
eco|5 months ago
mmaia|5 months ago
> A great misunderstanding accounts for public confusion about thinking machines, a misunderstanding perpetrated by the unrealistic claims researchers in AI have been making, claims that thinking machines are already here, or at any rate, just around the corner.
> Dreyfus' last paper detailed the ongoing history of the "first step fallacy", where AI researchers tend to wildly extrapolate initial success as promising, perhaps even guaranteeing, wild future successes.
https://en.wikipedia.org/wiki/Hubert_Dreyfus's_views_on_arti...
libraryofbabel|5 months ago
> A puzzling characteristic of many AI prophets is their unfamiliarity with the technology itself
> After reading these books, I began to question whether “hype” is a sufficient term for describing an uncoordinated yet global campaign of obfuscation and manipulation advanced by many Silicon Valley leaders, researchers, and journalists
red75prime|5 months ago