I work in medical research and know many healthcare practitioners. They often share anonymized stories about their patients and higher level summaries of patterns they see across their patient population or in their institution.
I couldn’t learn to be a doctor from these occasional stories, but I understand the intimate details of their work much better than I would from articles, especially the social side.
For example, my geneticist friend’s complaints about companies selling unregulated genetic tests helped me understand why doctors are so much more conservative than researchers when it comes to new and unregulated medical tech. Researchers see developing new tests as innovation, doctors as often injecting more noise and confusion into an already overwhelming system.
That was a crucial insight for me as a biomedical researcher thinking about how to make a clinical impact.
Communities like HN and some subreddits that have a mind meld culture are wonderful resources. I bookmark those comment sections for technologies I’m considering using or ideas about how to code, and consider the comment section a critical component of the post they’re discussing.
I am about 2/3 median income for a full time year round worker in the USA, though I assume median for reasonable definitions of “the west” is lower than for the USA.
To put things in perspective, you can look up putative prices for McDonald's in India at mcdonadsprices.com, claimed to be current as of January 8, 2024. The McSaver Chicken Kebab Burger Meal with Whole Wheat Bun is listed at 214.30 rupees, or $2.44. For a person with a monthly income of 5,000 rupees, this meal costs about 4% of their monthly salary.
For me, a PhD student, 4% of my monthly salary is about $143. So eating at McDonald's is essentially the equivalent of fine, upscale dining for the average person, and it makes sense that it would be nice inside since only the relative rich can afford to eat there.
Maybe it’s not the algorithm that sucks, but the interface - specifically that it conflates algorithm training with content consumption. Perhaps the main page should not update on your clicks, just show content. A separate interface should be used to pick content you want to see more or less of.
1It might be worth getting more explicit about vN’s exact argumentative steps and see if it’s really as ironclad as you think.
Humans have a finite amount of time to occupy the universe. In principle, control systems for nuclear weapons can be engineered to be arbitrarily reliable. The logic of MAD says that nuclear powers will not conduct a nuclear exchange. This line of argument suggests there is no deductive logical reason why nuclear war is inevitable between two nuclear powers. If we have such a war, it may be due to theoretically preventable failures, such as flawed systems. The existence of a possible reason a nuclear exchange might occur without a first strike is far from compelling justification to do one.
My current model of teaching and learning (self-teaching) is that to be effective, it needs to target a specific piece of information the student is immediately ready for. I want a word for such pieces of information, so let's call them useable bits. In a sentence, the teacher or learner's job is to present a stream of useable bits to the student with a minimum of non-useable bits. Most of the time, the vast majority of information the student receives is non-useable bits, and trying to sift the useable bits from that stream causes overwhelm and confusion.
Effective learning involves purifying information streams to contain a higher concentration of useable bits. There are multiple strategies for this:
- Fast sifting: Learn how to more quickly and easily sift useable bits from a stream of non-useable bits. I think this is most students' default strategy, developed as a survival tactic in school where it's their only obvious option. It is unlikely to establish a new foundation, but instead establish a hodgepodge of trivia-like, quickly-forgotten extensions to the student's pre-existing foundational knowledge, resulting in precisely the kind of deeply inadequate learning outcomes we observe as a rule from the education system.
- Building from a foundation: Structure the learning task so that the student's next useable bits that are also relevant to the student's priorities are always apparent -- we always know what the student is ready for next and we give just that information to them. This requires having a foundational grasp of the subject so that identifying the next useable bit that's also most relevant to the student's interest is obvious.
- Digging a rabbit hole in which to lay a foundation: Focus on the first point of apparent uncertainty (the first non-useable bit), and recursively drill into it definitionally until that first non-useable bit becomes useable. This may be a deep rabbit hole. However, it hopefully results in establishing fundamental topic knowledge that will eventually allow a more focused approach to learning specific topics within the domain.
Taking that literally, there are a tremendous number of acts that might cost others or that might be only appropriate in context. Having to specially flag everything fitting that criteria seems onerous.
More generally, I think it’s important to think through what the next issues become after a norm like this is implemented. I anticipate you’ll have wildly asymmetric self-flagging based on social anxiety, the in-group popularity of the person or their ideas. Specifically, there will be some popular people who can freely rant and psychologize with no flagging, never getting called out, plenty of upvotes and no mod action when it happens online. But now there will be explicit grounds for sanction when less popular people fly against the ingroup and a built in reporting bias reinforcing locally favored views.
To be clear, I think that the sort of self flagging you describe can be contextually very useful. I just resist the idea of making it a blanket, context-free rule.
One think I think might be a useful compromise would be to add a “rant/uncharitable/psychologizing” emoticon as an option for LessWrong comments, possibly along with emoticons related to whether the comment is or is not adding useful context/is relevant/is more helpful than harmful or vice versa. This gives a way for the community to share information about how they perceive comments like these, giving the advantage you were looking for in having such rants be labeled as such. It allows the original ranter to say what they want to say. It gives them feedback on how they’re perceived rather than forcing them to make assumptions. And I think that it’s easier to unfavorably emoticon a high status figure’s post or comment than to actually write out a comment that provides a wider attack surface for punishment.
For in person interactions obviously this is no solution, so take this as all primarily being my opinions on online discourse.
Better I think would be to talk about a few of the points from the book that you thought were most important. This shows you understood the book and which bits might be most interesting to your interlocutor.