On the other hand, if AI data centres all disappeared today, humanity would continue on completely fine.
246 karma · joined August 21, 2021
On the other hand, if AI data centres all disappeared today, humanity would continue on completely fine.
I think this post is a decent summary, the answer is a soft maybe: https://www.health.harvard.edu/mind-and-mood/should-i-worry-...
Second-gen tablets might increase dementia risk by a small-to-medium amount (there's almost certainly still a small degree of CNS activity, and we don't know what causes dementia in the first place), but researching it will be difficult. Dementia is hard to research because of how long it takes to develop, and it's poor coding within health data, and antihistamines are hard to research because they're not often prescribed and aren't available in the health data.
If it's a large effect, those factors wouldn't matter, but smaller risks are harder to detect and more sensitive to bias. If you want to minimise dementia risk, then reducing antihistamine use might be warranted, but you're probably better off addressing the risk factors we do know about: https://www.dementia.org.au/brain-health/risk-factors-develo...
Unfortunately the sequence of treatments and locations are usually enough to identify someone, especially if it's a rarer condition.
It can help a little bit in the early stages of drug design, but even if it was perfect (which it's not), there's a massive gap between understanding a protein structure, and understanding how a drug will or system will interact with it.
In a broader sense, understanding the structure of a protein is only a small part of drug development. Unfortunately biology is complicated, and we're an extremely far way away from solving it.
(As an aside, there are more complex extended release mechanisms than just delayed bead release - like lisfexamfetamine is a inactive prodrug, so cleaving the lysine off the amphetamine is rate limited. This has the effect of extended the duration of effect, and reduces the potential to abuse by snorting/iv/etc).
And regardless, increased acceptance and awareness of different gender identities can very plausibily explain increased numbers, not "social contagion". Calling it a contagion is pretty indicative of your underlying beliefs here.
This is a good overview of the literature: https://www.frontiersin.org/journals/neuroscience/articles/1...
https://www.accc.gov.au/by-industry/digital-platforms-and-se...
It's called the news media bargaining code. Technically speaking, the law isn't enforced since Google/Meta chose to voluntarily pay the link tax, rather than be put on the list that would force them to pay. But, at the end of the day it's the same effect.
And honestly with the government's track record when it comes to privacy and technology, I don't think they deserve the benefit of the doubt.
Are cystic fibrosis patients hooked on Trikafta? Are people with high blood pressure hooked on ace inhibitors? Or are they taking a medication to control their symptoms and improve their health?
Technically you don't need to take a drug to control your weight, and you could do it all naturally (although this is also debatable, given genetics). However, the reality is that most obese people don't have the time, money, circumstance, genetics or willpower to control their weight themselves. Ozempic is a shortcut to better health outcomes in these patients, why shouldn't they take it?
If you want to develop your skills, it's just as important to be aware of the things that aren't the answer, rather than just a single hyper-specific curated answer.
I'd personally recommend giving season 2 a shot, if you still don't like it then the shows probably not for you.
Something I feel Scott (and rationalists in general) tend to do is obfuscate their points in large walls of text, that allude to their actual reasons for writing without directly stating it. Aside from the beginning and end of the post, he never mentions the context or specifics, and just talks about broad counterarguments against selection bias in general. He doesn't bring up relevant specifics like "Aella does polls about sex to an audience she cultivated by doing porn", which seems like an obvious source of bias to me. Instead he gets the best of both worlds, if someone criticizes internet surveys he can point them to the post, without including any specifics that can be easily argued against. It requires a similarly sized wall of text to respond, which most people won't bother with. I personally used to argue that's just how he writes and it's not intentional, but stuff like the email leaks made me change my mind on that [1].
I do wish I'd picked a better example though, what I'm really trying to say is that Scott is definitely capable of analyzing a topic in bad faith. He has his biases like the rest of us, and they get infused into his writing.
He starts by stating that people say his surveys and Aella's Twitter polls (which he calls surveys) have selection bias, meaning the conclusions don't count.
He then goes on to say (paraphrasing): "people say surveys have selection bias, but don't think real scientific studies have selection bias" and in the next paragraph says "but scientific studies do have selection bias and that's ok." Note that in this section, he is implictly relating scientific studies with his and aellas surveys.
In the section that starts with "selection bias is disasterous if", he gives a narrow view of why and when it's bad: "only if you're doing a poll or census that should include everyone". He neglects to say the ways in which it's bad for literally all science (it's a massive problem in drug RCTs, but he literally uses RCTs as a point for why selection bias isn't so bad later on).
In the next few paragraphs he says that selection bias is fine for correlations, and gives some examples of when scientific studies have selection bias that we accept (I'm not going into details here because the post is long, and I'm on my phone).
So he's said why selection bias is present in science, and that it's only really bad for census's and polls. He then concludes, "hey guys stop saying surveys are bad because selection bias, science is also biased".
In this post he starts by bringing up a critism of Aella's 'research', which she uses data from Twitter polls for. He then implicitly equates surveys and scientific studies, and says "look, science is biased too, so selection bias isn't bad". He then concludes, "so stop saying surveys are a bad because of selection bias".
He might not literally say "twitter polls are exactly as good evidence as a scientific study", but the point of the post was to detract from the valid criticisms against his and Aella's posts that use survey/twitter poll data by saying "science does it too".