This is why I love LessWrong.
Thanks, I’m saving this if I ever get any symptoms, and I’m also considering taking some mebendazole as a purely preventative measure (I don’t remember that I’ve ever taken it, and I’ve been exposed to dirty work for years and years now).
source on my blog: https://sundaystopwatch.eu/some-thoughts-in-traffic/
(these are literally thoughts I had sitting in traffic and that relate to traffic, but you’re free to extract generalized life lessons from them if you want)
When someone cuts you off in traffic, you might get angry, but their behavior, their cutting-off-other-people-in-traffic personality guarantees that you will never be stuck behind them, unable to go faster.
The way to minimize killing animals on the road is to drive in the middle of the road, straddling two lanes (if the oncoming lane is empty). That way, you are maximizing the space (and therefore reaction time) between the road and whatever it is on the side of the road. This predisposes that both sides of the road are equally likely to contain crossing animals—if there’s a literal wall on one side, then it’s less killing per kilometer (kpk—nice measure eh?) to drive near that wall.
Google Maps, on the surface, appears to be an Earth element (Fire, Water, Earth, Air, Void), but it’s actually a Water element because when it detects congestion ahead, it reroutes you to the same destination, just like water finds another path. (I can’t decide if this thought is high, pseudo-deep or plain schizo.)
There are defensive drivers and offensive drivers. Defensive drivers worry about bad things happening, and imagine them happening before they do. So the difference isn’t “one speeds, the other one doesn’t”. In fact, defensive drivers also speed. The difference is what you’re thinking about. If you’re feeling really optimistic on your every drive, you’re likely an offensive driver. If you are imagining all the ways something could go wrong as you drive, you’re defensive. Thinking about the direction of oncoming animals is an example of pessimistic thinking, and therefore defensive driving.
Defensive driving is the obvious right choice.
Defensive driving has a bad effect though. Bad actors (offensive drivers) can do their thing unchallenged, such as cutting people off in traffic, because defensive drivers will have predicted their actions and already have adapted their maneuvers. Therefore the only thing that curtails offensive driving is offensivemaxxing, where an offensive driver is so offensive that nothing could be done to help them (e.g. driving at 100 km/h into a narrow corner and going offroad) OR other offensive drivers, which will cause crashes. It’s a sort of predator-prey dynamic, but offensive drivers are both the predator and prey, and defensive drivers are the background foliage.
I’ve changed my mind about driving cars with manual shifting. I no longer think that makes any sense, unless you’re racing or a hobbyist with retro cars. For everyday driving, automatic shifting is good, more relaxed, less cognitive overhead, and if traffic is safe enough, you can take a sip of water without worrying that you won’t be able to downshift in time for a corner or something.
Despite my strong occasional bouts of hate towards automobile traffic and optimization for automobile infrastructure, overall I still think that cars did a whole lot of good, despite all the CO2 emissions, lead poisoning, community disruption—both on the level of making streets unsafe for children to play on, and disrupting public transport as a joining force of the community. If we can choose between a world where people have their own robocarriage, and a world where you can’t go anywhere except on foot or by horse, even if all else isn’t equal (!), you’ll still probably choose to live in the robocarriage world… because people want to go places!
Computer networking and traffic engineering are essentially the same discipline, with differences in the protocol specifications (e.g. TCP vs. right-hand-side rule) and packet formats (e.g. datagrams vs. cars). Yet all the guys that I know that studied traffic engineering in college know nothing about protocols, or even that kind of thinking. You would expect that you’ll learn about e.g. Dijkstra’s pathfinding algorithm in computer science and in traffic engineering, but (from my experience with people in both disciplines), you only learn about it in CS.
The European version of the pickup truck is the cargo van with the pickup bed. It’s almost the same thing, actually it literally is the same thing. Yet there’s a sense in which a pickup truck is a car (a personal vehicle), and a pickup van is a van (a work vehicle), even when a pickup truck is used for work.
There’s an established path towards passing a regulation; there is not an established path towards discovering new technology. The first can fail, but you have a known way how it is done. The second can also fail, but you generally have no recipe to follow.
I meant “almost guaranteed (that you can pass it)”, not “almost guaranteed that it’ll work”. Meaning, you know you have recourse (though it might not work). As opposed to “not guaranteed (that there even will be any tech)”. Should’ve been clearer. Generally I agree with your comment.
Something like that, yeah
I don’t mean this only for group sizes, but good point, there could be a qualitative difference and simplifying is actually fundamentally changing the topic.
I don’t know, I still feel like it helps me figure out the core of a problem. However, I agree that asking if a proposed solution scales is important for the types of issues I listed in the examples.
Your strategy for AI risk seems to be “Let’s not build the sort of AI that would destroy the world”, which fails at the first word: “Let’s”.
I don’t have a strategy, I’m basically just thinking out loud about a couple of specific points. Building a strategy for preventing that type of AI is important, but I don’t (yet?) have any ideas in that area.
Time-slack isn’t rewarded with status that much, I think. Whenever someone can say “yeah, whenever’s fine” in response to somebody that can only make it for exactly 4.32 minutes every second full Moon but only in January, I rarely find that this person is awarded status, even implicitly. It’s basically taken for granted. Which reinforces your point that high-slack people don’t capture the upside that much.
And which, in turn, leads me to ask: is the status payoff enough even for a rough selection? I think not. To reliably select for high-slack people (and therefore create high-slack groups), even roughly, I think you need to explicitly require some X amount of slack (easy for time, difficult for emotions).
And, of course, to make the implicit explicit—which seems to be the point of your post.
Regarding 2 and 3: that’s the main practical perk of reading LessWrong, or as I’m inclined to call it now, SoonerRight.
Thanks everyone!
I agree, and am also confused with the idea that LLMs will be able to bootstrap something more intelligent.
My day job is a technical writer. I also do a bit of DevOps stuff. This combo ought to be the most LLM-able of all, yet I frequently find myself giving up on trying to tease out an answer from an LLM. And I’m far from the edge of my field!
So how exactly do people on the edge of their field make better use of LLMs, and expect to make qualitative improvements?
Feels like it’ll have to be humans to make algorithmic improvements, at least up until a point.