trentmkelly/LessWrong-43k huggingface dataset:
(Trying To) Study Textbooks Effectively: A Year of Experimentation
by DirectedEvolution — 2021-05-28T05:51:23.816Z

When I started studying the art of studying, I wanted to understand the role of book learning. How do we best learn from a textbook, scientific article, or nonfiction book? What can a student of average intelligence do to stay on top of their homework? Is it possible to improve your annual knowledge growth rate by one or two percent by learning how to learn? Should a motivated student take a maximizing or satisficing approach to their coursework? How many of the skills of a top scholar are strategic, collaborative, psychological, or involve merely a set of habits and technological proficiencies?

Fortunately, I started with the most esoteric of approaches, exploring visualization. I tried using a memory palace to memorize a textbook. It was vivid, fun, and creative. Exploring visualization helped me understand chemical diagrams, led me to invent a math problem, and made learning a lot more fun. But I simply couldn't jam that much detailed technical knowledge into my head. The method didn't help me pass my final exam, and I dropped it.

Posts from this era include Visual Babble and Prune, Using a memory palace to memorize a textbook, The point of a memory palace, Visualizing the textbook for fun and profit,

After that, I explored speed reading. I read the theory, experimented both with physical technique and speed reading apps, and kind of broke my reading habits developing this difficult-to-correct tendency to skim. This tendency to read too quickly persisted long after I'd dropped deliberate attempts at speed reading. I finally made some intellectual progress, which preceded correcting the reading habit itself, in The Comprehension Curve.

Then I explored the world of Anki and tried to use flashcards to memorize a textbook instead (or at least a few chapters). After simulating the sheer amount of flashcard review I'd have to do to keep a strategy like that up long-term, I dropped that too. I felt that forming memories of narrow facts (like the structure of RNA polymerase or the name of the 7th enzyme in glycolysis) was the costliest way to learn. And I found the achievement of world-class memory champions irrelevant to real-world learning, which just seems like an entirely different task.

Posts from this area (not all on flashcards specifically) include The Multi-Tower Study Strategy, Define Your Learning Goal: Competence Or Broad Knowledge, Progressive Highl...
Why Prefetch Is Broken
by jefftk — 2021-05-28T02:20:02.388Z

When coding a webpage, sometimes you know something is very
likely to be needed, even if it's not needed yet. You can give the
browser a hint:

<link rel=prefetch href=url>

The browser will take a note, and then when it doesn't have anything more
important to do it might request

url. Later on,
if it does turn out to need

url, it will already
have it.

For example, I wrote a slideshow where each slide was essentially:

Slide N:
<img src=img_N>
<link rel=prefetch href=img_N+1>

Prefetching the image for slide N+1 when viewing slide N made each
transition practically instant.

This works for images, but also works for CSS, JS, HTML, anything!
Or, at least, it used to.

The browser stores URLs it fetches in a cache. At its
simplest this looks like a big dictionary, from
url to the contents of that url:

a.test/js

javascript1

b.test/js

javascript2

Unfortunately, attackers can
abuse this to learn about your browsing on other sites, and all
the major browsers (Safari, Chrome,
Firefox)
now have partitioned their cache. This means if you are on
a.test and load a.test/js that JS will not
be reused if you go to b.test and load
a.test/js again. The dictionary's keys look like
(site, url):

a.test:a.test/js

javascript1

b.test:a.test/js

javascript1

b.test:b.test/js

javascript2

Even if the keys a.test:a.test/js and
b.test:a.test/js both have exactly the same JS bytes,
they need to be kept separate to avoid a privacy leak.

So now imagine you are a modern browser visiting a.test
and you encounter:

<link rel=prefetch href=b.test/index.html>

Where should you store it in your cache? Well, it depends what the
user is going to do. If they are going to click on a link to

b.test/index.html, then when they need the HTML they will
be visiting

b.test and so you want to store it as

b.test:b.test/index.html. On the other hand, if it's
going to load in an iframe, the user will still be on

a.test and so you want to store it as

a.test:b.test/index.html. You just don't know. Just
guess?

The guess is a risky one: if you store it under the wrong key then
you'll have fetch the same resource again just to store it under the
right key. Users will see double fetching.

It turns out browsers guess differently here. I made test pages
(iframe,
new
page) and while Firefox guess...
Aphantasia
by Crackatook — 2021-05-28T01:55:33.951Z

James_Miller mentioned Aphantasia and it blows my mind: "What?...imagination has been my greatest portion of thinking...and there are people who cannot imagine..." To me, weak but constant visualization & audioization come right after reading any texts, and I stop reading when my brain can't visualize properly. I once suspected my sister(very young at that time) does not like reading books because she was not used to imagine while reading.

How do people with Aphantasia read texts and process while studying?
Predict responses to the "existential risk from AI" survey
by Rob Bensinger — 2021-05-28T01:32:18.059Z

I sent a short survey to ~117 people working on long-term AI issues, asking about the level of existential risk from AI; 44 responded.

In ~6 days, I'm going to post the anonymized results. For now, I'm posting the methods section of my post so anyone interested can predict what the results will be.

[Added June 1: Results are now up, though you can still make predictions below before reading the results.]

Methods

You can find a copy of the survey here. The main questions (including clarifying notes) were:

1. How likely do you think it is that the overall value of the future will be drastically less than it could have been, as a result of humanity not doing enough technical AI safety research?

2. How likely do you think it is that the overall value of the future will be drastically less than it could have been, as a result of AI systems not doing/optimizing what the people deploying them wanted/intended?

_________________________________________

Note A: "Technical AI safety research" here means good-quality technical research aimed at figuring out how to get highly capable AI systems to produce long-term outcomes that are reliably beneficial.

Note B: The intent of question 1 is something like "How likely is it that our future will be drastically worse than the future of an (otherwise maximally similar) world where we put a huge civilizational effort into technical AI safety?" (For concreteness, we might imagine that human whole-brain emulation tech lets you gather ten thousand well-managed/coordinated top researchers to collaborate on technical AI safety for 200 subjective years well before the advent of AGI; and somehow this tech doesn't cause any other changes to the world.)

The intent of question 1 *isn't* "How likely is it that our future will be astronomically worse than the future of a world where God suddenly handed us the Optimal, Inhumanly Perfect Program?". (Though it's fine if you think the former has the same practical upshot as the latter.)

Note C: We're asking both 1 and 2 in case they end up getting very different answers. E.g., someone might give a lower answer to 1 than to 2 if they think there's significant existential risk from AI misalignment even in worlds where humanity put a major civilizational effort (like the thousands-of-emulations scenario) into technical safety research.

I also included optional fields for "Comments / questions / objecti...
AXRP Episode 7.5 - Forecasting Transformative AI from Biological Anchors with Ajeya Cotra
by DanielFilan — 2021-05-28T00:20:10.801Z

Audio unavailable for this episode.

This podcast is called AXRP, pronounced axe-urp and short for the AI X-risk Research Podcast. Here, I (Daniel Filan) have conversations with researchers about their papers. We discuss the paper and hopefully get a sense of why it’s been written and how it might reduce the risk of artificial intelligence causing an existential catastrophe: that is, permanently and drastically curtailing humanity’s future potential.

If you want to shape the development and forecast the consequences of powerful AI technology, it’s important to know when it might appear. In this episode, I talk to Ajeya Cotra about her draft report “Forecasting Transformative AI from Biological Anchors” which aims to build a probabilistic model to answer this question. We talk about a variety of topics, including the structure of the model, what the most important parts are to get right, how the estimates should shape our behaviour, and Ajeya’s current work at Open Philanthropy and perspective on the AI x-risk landscape. Unfortunately, there was a problem with the recording of our interview, so we weren’t able to release it in audio form, but you can read this transcript of the whole conversation.

Note that content surrounded by [square brackets] was added at the time of transcription.

Daniel Filan:
Hello everybody, today I’ll be speaking to Ajeya Cotra, a senior research analyst at Open Philanthropy, which is a grant-making organization that supports work to reduce AI existential risk [among other things]. Before joining Open Philanthropy she studied electrical engineering and computer science at UC Berkeley, where she founded the Effective Altruists of Berkeley student group, and also taught a course on effective altruism. Today we’ll be talking about her work on forecasting when transformative AI might be developed, and how that might influence grant recommendations. Ajeya, welcome to the show.

Ajeya Cotra:
Thank you, great to be here.

Daniel Filan:
Great. So I guess we’re going to be mainly talking about this draft report on forecasting. I believe it’s called forecasting transformative AI?

Ajeya Cotra:
Forecasting Transformative AI From Biological Anchors.

Daniel Filan:
Exactly that one. So just briefly, can you summarize what you were trying to do in this report and how you went about doing it?

Ajeya Cotra:
Yeah. So Open Philanthropy is interested in reducing risk...
The Homunculus Problem
by abramdemski — 2021-05-27T20:25:58.312Z

(This is not (quite) just a re-hashing of the homunculus fallacy.)

I'm contemplating what it would mean for machine learning models such as GPT-3 to be honest with us. Honesty involves conveying your subjective experience... but what does it mean for a machine learning model to accurately convey its subjective experience to us?

You've probably seen an optical illusion like this:

The checker shadow illusion. Although square A appears a darker shade of gray than square B, in the image the two have exactly the same luminance. Source: Wikipedia

You've probably also heard an explanation something like this:

"We don't see the actual colors of objects. Instead, the brain adjusts colors for us, based on surrounding lighting cues, to approximate the surface pigmentation. In this example, it leads us astray, because what we are actually looking at is a false image made up of surface pigmentation (or illumination, if you're looking at this on a screen)."

This explanation definitely captures something about what's going on, but there are several subtle problems with it:

It's a homunculus fallacy! It explains what we're seeing by imagining that there is a little person inside our heads, who sees (as if projected on a screen) an adjusted version of the image. The brain adjusts the brightness to remove shadows, and adjusts colors to remove effects of colored light. The little person therefore can't tell that patch A is actually the same color as patch B.
Even if there was a little person, the argument does not describe my subjective experience, because I can still see the shadow! I experience the shadowed area as darker than the unshadowed area. So the homunculus story doesn't actually fit what I see at all!
I can occasionally and briefly get my brain to recognize A and B as the same shade. (It's very difficult, and it quickly snaps back.)

My point is, even when cognitive psychologists are trained to avoid the homunculus fallacy, they go and make it again, because they don't have a better alternative.

One thing the homunculus story gets right which seems difficult to get right is that when you show me the visual illusion, and explain it to me, I can believe you, even if my brain is still seeing the illusion. I'm using the language "my brain" vs "me" precisely because the homunculus fallacy is a pretty decent model here: I know that the patches are the same shade, but my brain insists...
99% shorter
by philh — 2021-05-27T19:50:03.532Z

I listen to podcasts while doing chores or at the gym, and often feel like I'm learning something but then can't really remember anything afterwards. So for the past ~month I've been doing an experiment where I write brief summaries of them afterwards, usually same-day but sometimes a bit later. Generally I avoid all forms of fact checking, both "what did the episode say" and "what is actually true", though I don't stop myself if I feel like doing it.

I've been posting them to my shortform on LessWrong. Mostly in reply to a single comment for tidiness, but two of them I accidentally posted to the top of the thread and one as a reply to another. Initially that was just because I wanted to be able to write them from both my work and personal laptops. (This blog is published through git. I don't have the repo on my work laptop, and probably shouldn't do.) But I kind of like it. A downside is it's slightly less convenient to include episode numbers or air dates or even titles unless I remember them. So I might be less consistent about that, though it feels good to have a fairly straightforward way to look up the episode given my summary.

I've skipped all the fiction podcasts I listen to, because that's not why I listen to fiction. Also most interviews, those seem generally hard to summarize, though it would probably be reasonable to extract a few individual points. And one Planet Money episode seemed like it would be irresponsible to summarize carelessly, and I didn't feel like trying to be careful about it. But I've summarized every episode of 99% Invisible and History of English, and all but that one episode of Planet Money, that I've listened to in this time. Also one episode of Rationally Speaking and one of Corecursive.

I'm not really sure what this experiment was trying to test. I was curious, so I did it. Some things I've maybe vaguely learned: first, I think I can generally do a decent summary. I frequently get distracted for a few seconds at a time, but there's a difference between that and being actually distracted, and I think it shows. (I listened to 99% Invisible, "Tanz Tanz Revolution", while looking at parking restrictions in my area and anticipating my evening plans. There's significant parts of that episode that just rolled right past me.) I don't think you could reliably pick out the episodes I didn't do same-day, I mostly don't even remember myse...
Data on forecasting accuracy across different time horizons and levels of forecaster experience
by CharlesD — 2021-05-27T18:53:07.884Z

Cross posted from the EA Forum

Key Points

Forecasting well is a valuable skill for many purposes and people, including for EA organisations aiming to identify which areas they should focus on and what the outcomes of various initiatives would be.
There is a limited public record of people making scored forecasts over time horizons greater than ~1 year. Here I use data from PredictionBook and Metaculus to study performance of predictions over different time horizons. I also looked at performance between users with different levels of forecasting practice.
When looking at individual predictors, it seems that a very common failure mode among newer or less dedicated predictors is overconfidence, and that it is more prevalent than underconfidence across most subgroups.
Across both PredictionBook and Metaculus, there seemed to be a significant bias towards overestimating the chances of positive resolution. This effect seemed to get stronger as time to resolution increased.
At least in the PredictionBook data, there was some weak evidence to suggest prediction performance improves with making more predictions, but there were too many confounding factors here to draw any confident conclusion.
The conclusions I was able to draw from this were limited, and working to improve this by expanding the amount and quality of data available for analysis like this seems worth doing.

This post draws a lot on niplav's

Range and Forecasting Accuracy

, not least for much of the code used to extract the PredictionBook forecasts, and also in identifying the most promising sources of useful data.

I think that this post is probably most useful to individuals making forecasts being aware of common failure modes and attempting to learn from them, and informing decision makers about these failure modes also, rather than attempting to provide those looking to use forecasts with e.g. a transform they should apply to long term forecasts.

Background

There has been a great deal of interest in forecasting in the EA community in recent years, particularly with the prominence of longtermist thinking. It is clearly of great interest that we be well equipped to make predictions about future events, and to understand the accuracy and failure modes of such predictions. Additionally, many of the questions we care most about will have long time horizons, therefore any evidence we can gain which helps us bec...
What's your visual experience when reading technical material?
by DirectedEvolution — 2021-05-27T18:34:42.442Z

In my never-ending quest to understand the best way to read a textbook, I'm back to where I started - exploring the importance of visual imagination. When you read technical material, such as science or math, or posts on rationality, to what degree do you visualize the text? Here are some possibilities, but no need to confine yourself.

Is your visual imagination "permanently off," so that you experience the concepts in a symbolic or diagrammatic manner?
Can you activate your visual imagination when you choose, but you're not in the habit?
Is your visual imagination for STEM material a consistent aspect of how you read?

Beyond this, do you feel that you'd get a lot out of being more able to visualize text, or having a more active visual imagination? Have you noticed any change in your ability to visualize over time?
A Review and Summary of the Landmark Forum
by reviewer — 2021-05-27T18:22:15.363Z

(This post is from a long-time member of the rationalist community - I may or may not be an active poster on Less Wrong. I’ve messaged a moderator and asked if they would be willing to make a comment to confirm that this is the case.

Landmark has copyright on their course content and they have trademarked terms like Always/Already Listening and Rackets, which is important to understand for legal reasons.

I’m also going to attach a spoiler alert as understanding the techniques might make them less effective. But that said, my recommendation is that if you are considering the forum then you should understand exactly what you are signing up for)

After attending the Landmark Forum, I was completely shell-shocked at having encountered some powerful psycho-social technology unlike anything I’d ever seen before. They seemed to have a powerful ability to change how people viewed the world. At the same time, I felt troubled by some of the methods they used to persuade us to invite our friends and family to do the forum. Ironically, if they hadn’t tried so hard, I would have recommended the forum in a heartbeat. But given that they did, I would strongly recommend that anyone who is considering going do their research before signing up and ensure they are appropriately mentally prepared. I've tried to make the main body of the analysis as objective as possible, but there were some points at which I felt the need to comment.

What happened and the stories we tell ourselves

The core idea of Landmark is that we are trapped within and held back by the stories that we tell ourselves. For the most part, we aren’t even aware that we are operating from within these narratives, but they serve as excuses and determine many of our choices.

For example, imagine Derek had a rough childhood and was frequently beaten up by other kids until he started working out and training in martial arts. Years later, Derek is married and has trouble sharing openly with his wife, which pushes them to the verge of divorce.

A Landmark forum leader would ask Derek what he told himself back when he was being kicked into the ground. After some back and forth, Derek might eventually say that he told himself "I was weak and needed to become strong to survive". The forum leader might suggest that this is why he is unable to share: sharing makes Derek feel weak and he has a story that he has to be strong. Even tho...
How likely is our view of the cosmos?
by Yitz — 2021-05-27T16:35:25.683Z

In terms of what we see in the night sky, are we a statistical anomaly compared to the average star system? That is, what percentage of stars with potentially habitable planets exist close enough to other stars to see a significant number of them in the night sky, have a mostly unimpeded view of other galaxies beyond their own, and aren’t in any sort of “cosmic fog” (inside a nebula, etc.) unable to see much of anything? Would that percentage be different if we included uninhabitable star systems? What about if we included all star systems from the beginning to the “end” of the universe (aka the point at which no more stars are being produced, for the purpose of this question), not just the universe as it is today?

I’m not sure how important it is that these questions be answered, but I would definitely be interested if it turns out that our view of the heavens is a statistically unlikely one. My guess would be that we’re experiencing one of the more common views of the universe, but I could imagine it being possible that most habitable planets are likely to exist at a time when views of other galaxies are not available. If so—especially if our view is remarkably unlikely—what would the implications of that be?