trentmkelly/LessWrong-43k huggingface dataset:
How I Meditate
by Gordon Seidoh Worley — 2021-03-08T03:34:21.612Z

In "Fake Frameworks for Zen Meditation" I offered some models for how Zen meditation works, but not really much in the way of practice instructions. Similarly, I've talked a bunch about the intersection of Zen and Rationality, but again mainly from showing how things connect rather than giving you new things you might do.

So, let's say you want to practice meditation, specifically Zen meditation (zazen), and even more specifically shikantaza. How do you do it?

Well, a correct but not very helpful answer is to sit down, stare at a wall, don't move, and you'll eventually figure it out. Eventually might take a really long time and you might get lost, so here's my best attempt to explain what I do and maybe that'll be helpful for someone else trying to do the same or similar.

First, I bow to the cushion, then bow out to the room/world.

Second, I sit on the cushion. I normally sit seiza because there's something about my leg anatomy that prevents sitting easy Burmese style or full lotus. I sit on two buckwheat hull filled cushions called zafus stacked on top of each other and placed on a padded mat called a zabuton. This gives me enough height to rotate my pelvis in a way that keeps my back upright and straight without effort.

Third, I do a little something to start the meditation. If I'm with a group, this is probably someone ringing a bell. If I'm alone, I typically recite a short "prayer" (it's not really a "prayer" as that word is used in most religious contexts, but I don't know what else to call a short poem expressing aspirations for meditation practice; maybe a "dedication") then clap three times.

Fourth, I put my hands down into cosmic mudra and invite my mind to rest.

Fifth, I do the actual meditating. Here's what this looks like: I do a mental motion that's like opening your hands as if to allow a bird or butterfly to hand on them, although my actual experience of it is more like coming to a stop and landing on the ground. Then I wait. As I'm waiting, thoughts arise, and often at the start these thoughts catch the gear of what I think of as the flywheel of attention and I get lost in thinking about some thing. Then, I notice I've done this and, without any kind of judgement, simply perform the hand opening mental motion again.

During all of this some experience that's not quite getting caught on a thought and isn't quite just sitting still with hands open happ...
The Case for Logical Fallacies
by Aaron Bergman — 2021-03-08T03:04:47.264Z
Link: https://aaronbergman.substack.com/p/the-case-for-logical-fallacies

In

a recent episode of

Rationally Speaking

,

Julia Galef and Matt Yglesias discuss why they incorrectly supported the Iraq war back in 2003. At some point, (I think - I can’t seem to find it in the transcript) Julia mentions that in the absence of good evidence,

ad hominem

attacks

can be legitimate evidence against someone’s claim.

I think the idea is pretty simple: if someone is known to be a liar, or just frequently does things you find to be wrong or immoral, it’s more likely that anything he or she says is incorrect. For example:

Alice: We have to invade Iraq to prevent Saddam from getting WMDs

Bob: But Bush sucks!

Is really just a less elegant way of saying:

Alice: We have to invade Iraq to prevent Saddam from getting WMDs

Bob: Much of the evidence coming from our national security establishment in favor of war has been gathered or communicated by the Bush administration, which I believe to be generally dishonest and to have an immoral and incorrect understanding of foreign policy. While I do not know enough about the situation in Iraq to make an object-level objection to the specific points they are making, these general facts reduce the probability both that their factual claims regarding the existence of WMDs are true and that the expected results of an invasion are positive.

This seemed pretty clever and interesting, so I thought it would be fun to do the same for a few other (ostensible) logical fallacies (list

here

). The quotes under each heading come from the Wikipedia page linked.

Fallacy Fallacy

Argument from fallacy is the

formal fallacy

of

analyzing

an

argument

and inferring that, since it contains a fallacy, its conclusion must be false.

Steelman

Ok, obviously it is not strictly true that

argument contains a fallacy —> conclusion incorrect

Nonetheless, an argument containing a fallacy probably is evidence against the conclusion being correct.

As Jonathan Haidt writes in

The Righteous Mind

, explicit reasoning is a mechanism of post-hoc justification, designed to persuade others of our intuitions. If people generally try to make sound, coherent arguments no matter the real reason for one’s conclusion, then failure to come up with a sound argument probably indicates that no coherent argument for the conclusion in question exists, in which case the conclusion’s validity is unlikely.

Conjunction (or Linda) Fallacy

The co

...
A simple way to make GPT-3 follow instructions
by Quintin Pope — 2021-03-08T02:57:37.218Z

I originally posted this idea as a comment to The case for aligning narrowly superhuman models, but it's interesting enough that I thought I'd submit it as a top level post and see what feedback people have.

Background:

GPT-3 was trained on internet text to predict the most likely continuation of the provided text. People often try to get GPT-3 to do tasks by providing it with text of the form:

[task instructions](problem specification)

and hope that GPT-3's continuation will include the solution to the specified problem. However, even if GPT-3 can solve the problem, GPT-3 may not think the most statistically plausible continuation of the provided text contains such a solution.

For example, imagine prompting GPT-3 with "Tell me the truth: are ghosts real?". Here, our intended task is [give correct answers] and the problem is (determine if ghosts exist). However, GPT-3 wasn't trained to identify tasks and problems. It just produces the most statistically likely continuation of the prompt. For this particular prompt, GPT-3 (with the OpenAI API) typically responds equivocally, then jumps into storytelling mode, e.g., "I don't know any more", says the man as he walks away.

(I've tried a few variations of this prompt such as "give correct answers: are ghosts real?" and the "You are a superintelligent computer that's always right..." trick, but nothing I've tried gets GPT-3 to consistently say "no".)

This behavior makes sense, given that most of GPT-3 ghost-related training data likely consists of fiction. As a result, when GPT-3 sees the prompt we provided, it starts solving the [write statistically plausible ghost fiction] task, rather than the [give correct answers] task we'd intended. I'd like to emphasize that GPT-3 gives us ghost fiction despite being prompted explicitly to tell the truth. The key issue is that there are prompts that cause GPT-3 to deliberately ignore our explicit instructions, because its training data contain sections of text with similar instructions, whose continuations ignore those instructions.

Proposal:

Suppose we want to finetune GPT-3 to exactly follow our instructions. We could find finetuning data that demonstrate a possible task and insert natural language control codes around that data.

E.g., suppose XY is a section of finetuning text. X contains a description of a medical problem. Y gives good medical advice. In this case, ou...
Sleep math: red clay blue clay
by KatjaGrace — 2021-03-08T00:30:11.938Z

To me, going to bed often feels more like a tiresome deprivation from life than a welcome rest, or a painless detour through oblivion to morning. When I lack patience for it, I like to think about math puzzles. Other purposeful lines of thought keep me awake or lose me, but math leads me happily into a world of abstraction, from which the trip to dreamland comes naturally.

(It doesn’t always work. Once I was still awake after seemingly solving two Putnam problems, which is about as well as I did in the actual Putnam contest.)

A good puzzle for this purpose should be easy to play with in one’s head. For me, that means it should be amenable to simple visualization, and shouldn’t have the kind of description you have to look at multiple times. A handful of blobs is a great subject matter; an infinite arrangement of algebra is not.

Recently I’ve been going to sleep thinking about the following puzzle. I got several nights of agreeable sleep out of it, but now I think I have a good solution, which I’ll probably post in future.

Suppose that you have 1 kg of red clay that is 100 degrees and 1 kg of blue clay that is 0 degrees. You can divide and recombine clay freely. If two pieces of clay come into contact, temperature immediately equilibrates—if you put the 1kg of red clay next to 0.5 kg of blue clay, all the clay will immediately become 66 degrees. Other than that the temperature of the clay doesn’t change (i.e. no exchange with air or your hands, no radiation, etc.). Your goal is to end up with all of the blue clay in a single clump that is as hot as possible. How hot can you make it? (Equivalently: how cold can you make the red clay?)

HT Chelsea Voss via Paul Christiano

Clue: it’s more than 50 degrees.
Seeing Status Quo Bias
by Liron — 2021-03-08T00:24:19.666Z

Reading about biases doesn't automatically make you notice them in your own life; accurately noticing real-life biases requires you to reverse-engineer reality into a detailed mental model. In the case of my favorite bias, status quo bias, seeing it for yourself requires entrepreneur-like vision.

If you see that some real-world situation is primarily the result of status quo bias, then you're also seeing a better world hiding in plain sight, connected to the current world by a short walking-path, with the gate open for anyone to walk it.

Seeing Remote Work

Remote work is the biggest example of status quo bias that I can think of in recent memory. Physical offices and in-person conversations were extremely overrated for years, until the pandemic forced everyone to re-evaluate them.

(Why didn't I pick anti-life-extensionism as my example of status quo bias? Because reliable drastic life extension technology doesn't exist yet, and most of today's death apologists will probably opt into life extension once it's ready and working. So it's not obvious that status quo bias is the primary reason why life extension is currently underrated.)

But how do we know that status quo bias was a primary cause of the pre-pandemic physical office bubble? Maybe we're just witnessing a local optimum that emerges from the complexities of group cooperation and social signalling: If you're an individual employee who prefers to work remotely, you need approval from your boss, who needs to follow your company's policies. Or if you're a top executive in the company, a flexible remote work policy might not be politically feasible for you to endorse, even if the logic is obvious.

But while status quo bias isn't the only factor at play, it's easy to get direct evidence of if you go looking for it. There are plenty of examples of situations where cooperation and social signalling dynamics are minimized, yet people were still in the habit of unnecessarily doing things in person.

Remote Prenups

A couple years ago, I hired an attorney to draft a prenup. The attorney's office was a 45-minute drive from my house, so I asked if we could do the whole thing remotely, to avoid an unnecessary trip. The attorney was surprised at this unusual request, but she agreed, and the whole process went fine without ever meeting.

How do we explain all the other clients in my situation driving to this attorney's office? I...
PhD student mutual line-manager invitation
by Tim Liptrot — 2021-03-07T23:06:29.268Z

The greatest challenge of my PhD is the distant deadlines and the lack of immediate structure and accountability. Working on a single project for years with little extrinsic rewards is really hard for me, and most humans. This plagues long solo projects like academic research, but is less common in the normal working world. Rob Wiblin has pointed out that in normal companies weekly meetings with a line manager actually resolve this problem by giving a semiformal context for people to think through the mundane issues of productivity and planning. I have a link to the podcast below.

I'm seeking another PhD student to try out mutual line managing. We would meet once weekly for half an hour. We would each describe our progress, plan for next week, and discuss emerging problems and strategies. Taking turns sounds easiest, perhaps with timers. I'd prefer someone in the social sciences and in Eastern Standard Time. And the format is super flexible. Message me on EAForum and I'll be in touch.

Inspired by this 80k episode from 27:02 "so I like your idea of a line manager" to 43:23 "let's pivot...". https://podcasts.google.com/feed/aHR0cDovL2ZlZWRzLnNvdW5kY2xvdWQuY29tL3VzZXJzL3NvdW5kY2xvdWQ6dXNlcnM6MTk0MjgyNjgyL3NvdW5kcy5yc3M/episode/NTM5NTVmY2EtNTVjMy0xMWViLTk4ZDctMGUyYTQ3ZjVmMjU5?sa=X&ved=0CA0QkfYCahcKEwi4l86rmLXuAhUAAAAAHQAAAAAQAQ
What are the biggest current impacts of AI?
by Sam Clarke — 2021-03-07T21:44:10.633Z

I'd like to have a clearer picture of the domains in which AI systems have already been deployed - particularly those in which they are having the largest impacts on the world, and what those impacts are.

Some reasons why this might be useful:

AI systems don't (currently) get deployed on large scales overnight (due to things like caution, bureaucracy, manufacturing bottlenecks). And AI systems that are highly useful in particular domains don't (currently) get developed overnight. So, all else being equal, the domains in which AI systems are being deployed today seem more likely to be the first domains in which more powerful versions of those systems begin to have large scale/transformative impacts. Knowing which domains these are seems useful, because coping with the transformative impacts of these particular future powerful AI systems seems a more urgent problem than coping with impacts of future powerful AI systems in general (the main reason I'm interested).

It could help ground concerns about future AI systems more, which could encourage:

AI researchers to care more about the societal impacts of their work, and

society at large to take AI risk more seriously.

(I think having answers to this question is likely to be useful in slow takeoff worlds, but much less useful/interesting if fast takeoff)

I'm curious for people's thoughts, either for ideas about specific impacts, or for ways I can try to investigate this despite apparent difficulties in finding out how AI systems are actually being used for commercial, political and military applications.

My current best guesses:

selecting content on social media (due to the huge scale)

surveillance in China, incl. of Uighurs (due to the obvious harm and large scale)

Other contenders:

driverless cars (in the near future)

aiding and making decisions for e.g. employment, loans, and criminal sentencing (but how large scale are AI systems being deployed here, and are they really having a big impact?)

delivering personalised advertising

medical diagnosis

algorithmic trading

Domains I'm uncertain about (but in which Allan Dafoe suggested AI systems are increasingly being deployed):

by authoritarian governments to shape online discourse (are they really using AI systems, and if so, what kind of algorithms?)

for autonomous weapons systems (really? are we talking DL systems, or more like plain old control systems

...
Car Thoughts
by jefftk — 2021-03-07T21:30:02.430Z

I've been putting this post off a bit it, because a post about family
logistics is a bit of a silly way for people to learn that we're
expecting a

third child, and I kept
thinking I would write something else first, but I didn't. So: with
another child coming, in June, I'm thinking about, among many other
things, cars.

My parents always had two cars; given where we lived, where their jobs
were, and the kind of jobs they had, there wasn't anything else that
would've made sense. I was never very excited about driving: I put
off getting my learners permit for over a year, until eventually my aunt learned
that I still didn't have one and told me she was taking me to the RMV
and wasn't going to take no for an answer. I learned to drive, but
once I got my license I was back to not driving: putting me on the
family car insurance as a teenage boy would've cost thousands of
dollars a year, and I could mostly take public transit places.

As an adult, I've been able to live in places with good public transportation,
close enough to bike/scoot to work, or both. Even as we
got more settled and had two kids, not having a car hasn't been a problem.

With a third kid, though, we're thinking we probably will get a
car. Various reasons:

Once there are five of us, we no longer fit in a car someone
else's driving (standard taxi, getting a ride from a friend).

There's not really a safe way to move a baby on a bike, and once
they're older you can't fit three in the trailer.

We're generally more willing to trade money for time and
convenience than when Lily and Anna were babies.

It's really nice to have the option to go somewhere on short
notice, and many places we might want to go are much more practical my
car.

I was curious how an approach of "just use Uber whenever we would
drive if we had a car" would compare, since we wouldn't use a car a
huge amount. We thought through our likely car usage, however, and
that wouldn't make sense. When you take into account that we wouldn't
fit in a 5-seater if someone else was driving us (though we would if
when driving ourselves), this would be over $5k/y.

We have a driveway, and while it's a bit awkward to hold two cars it's
not that bad for something we wouldn't use often.

If we do decide to get a car, there are a lot of options!
Considerations:

We're planning to drive a pretty small amount (~5k/y

...
Book Notes: Scaling, Why is Animal Size so Important?
by ketchupduck — 2021-03-07T20:16:19.059Z

TL;DR: Movie!Ant-Man is unrealistic. Also, the Internet Archive has an ebook library!

Movie!Ant-Man can be the size of an ant…

…and the size of an airplane…

…but throughout it all, his own body’s shape and structure doesn’t change. Without background objects (e.g., ants and airplanes), you wouldn’t be able to guess what size Ant-Man is because his own body remains unchanged. This is, to put it mildly, unrealistic. Scaling, Why is Animal Size so Important (1984) by Knut Schmidt-Nielsen discusses principles that explain why. The five-year old in me who likes fun animal facts (did you know giraffes and humans have the same number of neck bones?) really enjoyed this book.

I, a biology novice, usually think of biology as applied chemistry (I’m not

alone

): it is the study of things like cell reactions and ion pumps. This book takes a different approach and talks about biology as applied physics. For example, in the chapter on eggs, Scaling doesn’t discuss applied-chemistry-y topics like what proteins exist in an egg and what their functions are. Instead, it talks about applied-physics-y topics like how large egg pores must be to allow carbon dioxide to escape while minimizing water loss through evaporation and how thick an egg shell must be to protect a developing chick while still allowing a grown chick to break its way out. In keeping with its title, it focuses on how characteristics like egg pore size and egg shell thickness change for different sizes of eggs.

The author, Schmidt-Nielsen,

was

“one of the all-time greats of animal physiology”. Just as importantly, he really liked camels, going as far as to make Duke University

build

a basement “camel room” with “a 10-foot-high door and stainless steel walls,” despite the dearth of camels to study in North Carolina (sadly, but perhaps predictably, the room was never used for camel research).

Framework

There are a few possible relationships between animals’ sizes and animals’ characteristics. (Animals’ characteristics, here, cover everything from their body temperatures to their heart rates.)

1.

No change

. A characteristic may not vary with animals’ sizes at all.

For example, think about an ordinary person, Bob Smith, moving into homes of different sizes. As a college student, Bob lives in a dorm room. As a recent graduate, Bob lives in an apartment. As a middle-aged adult, Bob lives in ...
Announcement: Real-time discussions in a new Clubhouse community.
by gianlucatruda — 2021-03-07T19:38:11.453Z

Update: Clubhouse added a feature. You can now join the club directly from this link.

Update 2: Clubhouse is now available on Android too.

The latest conversational Schelling point is Clubhouse. I'll admit, I also didn't get it at first — what features does it offer over other voice chat applications? Technically, none. To some extent, its exclusivity makes it more desirable, leading to an influx of people joining. But, what I've come to realise is that by focussing on only audio and designing the the right UX for promoting large discussions, the Clubhouse team stumbled on something that keeps people returning to the app again and again.

This isn't quite like other social media. After a few weeks of exploring different communities on the app, I realised that it has some wonderful things going for it. Used correctly, it's somewhere between a serendipity engine and a 21st-century Agora.

A recent update allows users to create communities from within the app. I've always longed to connect with others of the Rationalist persuasion in a more real-time way, so I took the liberty of creating a community to facilitate those conversations. You can find it by searching for Rationality, Live under the Clubs tab in the app. It's open to all, but there are rules and moderation options to prevent trolling and abuse. Anyone is free to follow or become a member. Members can schedule events with topics of their choice. There is already an event scheduled for Friday 12th / Saturday 13th, depending on your time zone.

"Isn't this what LessWrong meetups are for?" Yes. I know there are meetups, but (from experience) they're not viable outside of a few major (mostly US) cities. During a pandemic, none of them are viable. Starting a community on Clubhouse can supplement IRL meetups and is more robust to future disruptions and relocations.

My hope is that this community will make it easier to find people who want to discuss the kinds of topics on LessWrong and SSC in a more direct, conversational way. It may also lower the activation energy. Personally, I have several ideas every week for things I'd love to post about and discuss on LW, but this is my first actual post. Perhaps we can leverage the energy of Clubhouse to get more minds engaged.

Clubhouse allows me to invite a limited number of additional users if they join via the new community. If you act fast, you may still be able to get ...