Its been a good minute since the last thread like this, and with the techno-fascist dystopia being unleashed through the Trump administration, it felt like the time was right to bring this back.
Anyways, this is mostly the same idea as before - find books (or articles) that come down upon the superficial TESCREAL version of cool things like a ton of scientific bricks.
Gonna start this thread off with a few random examples I’ve already found:
-
The questions ChatGPT shouldn’t answer (Elizabeth Lopatto) - Goes heavily into OpenAI’s non-existent understanding of ethics, with a paragraph noting AI’s links to LessWrong and effective altruism. (EDIT: Originally said “non-existent understanding of physics” - thanks to @blakestacey for catching that)
-
The Fake Nerd Boys of Silicon Valley (Lyta Gold) - A deep dive into Silicon Valley’s fundamental misunderstanding of sci-fi. Not directly about TESCREAL, but still works wonders against it IMO.
-
“Main character syndrome” (Anna Gotlib) - Whilst primarily a critique of the titular phenomenon, it does also use longtermism/effective altruism as an example of such.
-
Questioning AI resource list - Exactly what it says on the tin.
You must log in or register to comment.
The Wikibooks book on statistics is surprisingly decent. Hopefully it inspires the reader to acknowledge that there are a lot more things to study apart from Bayes.
Larry Gonick’s Cartoon Guide to the Computer is in part a time capsule from a bygone age, and also an introduction to topics of enduring importance. It’s a comic book that explains how to design a Boolean circuit to implement an arbitrary truth table.
For an exposition of Bayesian probability by people who actually know math, there’s Ten Great Ideas About Chance by Persi Diaconis and Brian Skyrms (Princeton University Press, 2018). And for an interesting slice of the history of the subject, there’s Cheryl Misak’s Frank Ramsey: A Sheer Excess of Powers (Oxford University Press, 2020).
For quantum physics, one recent offering is Barton Zwiebach’s Mastering Quantum Mechanics: Essentials, Theory, and Applications (MIT Press, 2022). I like the writing style and the structure of it, particularly how it revisits the same topics at escalating levels of sophistication. (I’d skip the Elitzur-Vaidman “bomb tester” thought experiment for reasons.)
Another suggestion: Instead of indulging in LW-style Feynman worship, read James Gleick’s biography of him. It does a pretty good job covering the actual science while giving a warts-and-all portrayal of the man.
One area where I don’t know of good recommendations is theoretical computer science. I am not sure what to suggest that would accessibly teach topics like algorithmic/Kolmogorov information theory without sliding downhill into “we can automate the scientific method” crankery. Or, perhaps, which teaches the relevant concepts clearly and solidly enough to make it obvious that LW use of them is crankery.
Here is a comment by corbin with relevant recommendations:
Gödel makes everyone weep. For tears of joy, my top pick is still Doug Hofstadter’s Gödel, Escher, Bach, which is suitable for undergraduates. Another strong classic is Raymond Smullyan’s To Mock a Mockingbird. Both of these dead-trees are worth it; I personally find myself cracking them open regularly for citations, quotes, and insights. For tears of frustration, the best way to fully understand the numerical machinery is Peter Smith’s An Introduction to Gödel’s Theorems, freely available online. These books are still receiving new editions, but any edition should suffice. If the goal is merely to ensure that the student can diagonalize, then the student can directly read Bill Lawvere’s 1968 paper Diagonal arguments & Cartesian closed categories with undergraduate category theory, but in any case they should also read Noson Yanofsky’s 2003 expository paper A universal approach to self-referential paradoxes, incompleteness & fixed points. The easiest options are at the beginning of the paragraph and the hardest ones are at the end; nonetheless any option will cover Cantor, Russell, Gödel, Turing, Tarski, and the essentials of diagonalization.
On that note, I would recommend perusing Underwood Dudley’s Mathematical Cranks, not so much for the details of any math topic like trisecting an angle, but for the tone and psychology of the crank letters.
One possibility is Rebecca Weber’s Computability Theory (American Mathematical Society, 2012).
An anti-recommendation from another thread:
Having now refreshed my vague memories of the Feynman Lectures on Computation, I wouldn’t recommend them as a first introduction to Turing machines and the halting problem. They’re overburdened with detail: You can tell that Feynman was gleeful over figuring out how to make a Turing machine that tests parentheses for balance, but for many readers, it’ll get in the way of the point. Comparing his discussion of the halting problem to the one in The Princeton Companion to Mathematics, for example, the latter is cleaner without losing anything that a first encounter would need. Feynman’s lecture is more like a lecture from the second week of a course, missing the first week.
be like me and read the critique of pure reason and pierre bourdieu’s distinction, you’ll be ready for anything forever
Ran across a BlueSky thread that fits this perfectly - its a social sciences and humanities reading list on AI in education.
Since Adam Becker apparently has a new book out that lays into TESCREAL-ism and Silicon Valley ideology, I’m going to give an anti-recommendation regarding his prior book, What Is Real?, which is about quantum mechanics. Unlike the Sequences, it’s not cult shit. Instead, the ambience is more like Becker began with the physicist’s typical indifference to history and philosophy, and he somehow maintained that indifference all the way through writing a book about history and philosophy. The result fairly shimmers with errors. He bungles the description of the Einstein–Podolsky–Rosen thought experiment, one of the foundational publications on quantum entanglement and a major moment in the “what is quantum physics all about?!” conversation. He just fails to report correctly what the Einstein–Podolsky–Rosen paper actually says. He makes a big deal about how “hardly any women or people who aren’t white” appear in the story he’s told, but there were plenty of people he could have included and just didn’t — Jun Ishiwara, Hendrika Johanna van Leeuwen… — so he somehow made physics sound even more sexist and racist than it actually is. He raises a hullaballoo about how Grete Hermann’s criticism of von Neumann was unjustly ignored, while not actually explaining what Grete Hermann’s view of quantum mechanics was, or that she was writing about quantum entanglement before Einstein, Podolsky and Rosen! His treatment of Hermann still pisses me off every time I think about it.
The reanimation of pseudoscience in machine learning and its ethical repercussions (pdf link, open-access) is a wonderful take down of the epistemic abuses widespread in much of ML/AI.
Does this need to be marked NSFW? I think the joke about tagging the more serious posts that way ran its course a while ago, and we haven’t been sticking to it.
think there was a mod note a while ago (@dgerard? I think?) that nsfw was no longer required
I tagged it NSFW because the previous thread was tagged NSFW.
The description of “The questions ChatGPT shouldn’t answer” doesn’t seem to go with the text. Did you mean to link something else?
I didn’t mean to link something else, I just mangled my description. Thanks for catching it.
